Pinterest, Inc.

États‑Unis d’Amérique

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Type PI
        Brevet 189
        Marque 31
Juridiction
        États-Unis 182
        International 20
        Canada 13
        Europe 5
Date
Nouveautés (dernières 4 semaines) 1
2025 novembre (MACJ) 1
2025 octobre 1
2025 septembre 4
2025 août 4
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Classe IPC
G06Q 30/02 - MarketingEstimation ou détermination des prixCollecte de fonds 28
G06N 20/00 - Apprentissage automatique 27
G06F 16/2457 - Traitement des requêtes avec adaptation aux besoins de l’utilisateur 22
G06F 16/9535 - Adaptation de la recherche basée sur les profils des utilisateurs et la personnalisation 22
G06F 16/00 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet 21
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Classe NICE
09 - Appareils et instruments scientifiques et électriques 28
42 - Services scientifiques, technologiques et industriels, recherche et conception 27
45 - Services juridiques; services de sécurité; services personnels pour individus 27
38 - Services de télécommunications 25
35 - Publicité; Affaires commerciales 24
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Statut
En Instance 42
Enregistré / En vigueur 178
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1.

Accelerated training of a machine learning model

      
Numéro d'application 17325936
Numéro de brevet 12462200
Statut Délivré - en vigueur
Date de dépôt 2021-05-20
Date de la première publication 2025-11-04
Date d'octroi 2025-11-04
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Liu, Xi
  • Xu, Jiajing
  • Wang, Erzhuo

Abrégé

Systems and methods are presented for training a second machine learning model according to aspects of a trained first machine learning model. Processing features utilized by a training framework to train the first machine learning model are identified, and at least some of the processing features are combined with an initial set of training features to form updated training features. The updated training features are presented to a user for customization, resulting in customized training features. An executable training framework is configured with the customized training features and executed to train the second machine learning model.

Classes IPC  ?

  • G06N 20/20 - Techniques d’ensemble en apprentissage automatique
  • G06F 18/21 - Conception ou mise en place de systèmes ou de techniquesExtraction de caractéristiques dans l'espace des caractéristiquesSéparation aveugle de sources
  • G06F 18/214 - Génération de motifs d'entraînementProcédés de Bootstrapping, p. ex. ”bagging” ou ”boosting”
  • G06N 3/045 - Combinaisons de réseaux

2.

IDENTIFYING CONTENT ITEMS IN RESPONSE TO A TEXT-BASED REQUEST

      
Numéro d'application 19234699
Statut En instance
Date de dépôt 2025-06-11
Date de la première publication 2025-10-02
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Pancha, Nikil
  • Zhai, Andrew Huan
  • Rosenberg, Charles Joseph

Abrégé

Systems and methods for responding to a subscriber's text-based request for content items are presented. In response to a request from a subscriber, word pieces are generated from the text-based terms of the request. A request embedding vector of the word pieces is obtained from a trained machine learning model. Using the request embedding vector, a set of content items, from a corpus of content items, is identified. At least some content items of the set of content items are returned to the subscriber in response to the text-based request for content items.

Classes IPC  ?

  • G06F 16/483 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des métadonnées provenant automatiquement du contenu
  • G06F 16/44 - NavigationVisualisation à cet effet
  • G06F 16/45 - GroupementClassement
  • G06F 40/56 - Génération de langage naturel
  • G06N 20/00 - Apprentissage automatique

3.

VISUAL OBJECT GRAPHS

      
Numéro d'application 19222859
Statut En instance
Date de dépôt 2025-05-29
Date de la première publication 2025-09-18
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Kim, Eric
  • Kislyuk, Dmitry Olegovich

Abrégé

Disclosed are implementations that enable the linking or connection of objects and different scenes in which those objects are represented. For example, a corpus of scenes (e.g., digital images) that include a representation of one or more objects may be processed using the disclosed implementations to segment from those scenes the individual objects represented in those scenes. The disclosed implementations may further determine clusters of visually similar object segments and form object clusters for those object segments. The scenes that include those object segments are also linked to the object cluster. With scenes linked to different object clusters, a user may select one or more query objects or a query scene and be presented with other scenes that include visually similar objects, even though the overall scenes may be visually different.

Classes IPC  ?

  • G06F 16/55 - GroupementClassement
  • G06F 17/16 - Calcul de matrice ou de vecteur
  • G06F 18/22 - Critères d'appariement, p. ex. mesures de proximité
  • G06F 18/23 - Techniques de partitionnement
  • G06T 7/10 - DécoupageDétection de bords
  • G06V 20/30 - ScènesÉléments spécifiques à la scène dans les albums, les collections ou les contenus partagés, p. ex. des photos ou des vidéos issus des réseaux sociaux

4.

DATA EXTRACTION APPROACH FOR RETAIL CRAWLING ENGINE

      
Numéro d'application 19221357
Statut En instance
Date de dépôt 2025-05-28
Date de la première publication 2025-09-18
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Aggarwal, Amit
  • Zaytsev, Andrey
  • Gilfanov, Ruslan

Abrégé

A computer system extracts product data from a website and correlates product records from multiple sources to one another as corresponding to the same product. A website is crawled efficiently by rendering webpages using a virtual browser that ignores blacklisted elements, extracts data from objects without rendering, and suppressing retrieval of remote resources. Data is extracted according to engine control statements including a selector and extractor. A website may be crawled repeatedly and changes in extracted data may be detected and flagged. Engine control statements may be automatically changed in response to detecting a change in the configuration of the website. Images of product records may be correlated with one another by first comparing text of the product records and selecting images for comparison based on composition. Images are compared using a machine learning model. Images determined to be similar may be presented to a human for a correlation decision.

Classes IPC  ?

  • G06F 16/951 - IndexationTechniques d’exploration du Web
  • G06F 16/958 - Organisation ou gestion de contenu de sites Web, p. ex. publication, conservation de pages ou liens automatiques
  • G06Q 30/0201 - Modélisation du marchéAnalyse du marchéCollecte de données du marché

5.

PINTEREST PRESENTS

      
Numéro de série 99385962
Statut En instance
Date de dépôt 2025-09-10
Propriétaire Pinterest, Inc. ()
Classes de Nice  ?
  • 35 - Publicité; Affaires commerciales
  • 41 - Éducation, divertissements, activités sportives et culturelles

Produits et services

Advertising and promotional services; Arranging and conducting special events for commercial, promotional or advertising purposes Arranging and conducting of conferences in the field of advertising, marketing, e-commerce, software, and mobile applications; Educational services, namely, conducting programs in the field of advertising, marketing, e-commerce, software, and mobile applications

6.

END-TO-END TRAINED GENERATIVE SLATE RECOMMENDATION MODEL

      
Numéro d'application 18592099
Statut En instance
Date de dépôt 2024-02-29
Date de la première publication 2025-09-04
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Agarwal, Prabhat
  • Pancha, Nikil
  • Xu, Jiajing
  • Zhai, Andrew Huan

Abrégé

Described is an end-to-end generative recommendation model configured to determine a slate of content items to present to a user and the training thereof. The slate recommendation model may employ a generative model (e.g., generative transformer-based model, etc.) that is trained employing a multi-stage training approach. First, a generative model may be trained to learn a sequence model configured to generate a sequence of content items. The trained model may then be fine-tuned to better learn a distribution of slate recommendations. After fine-tuning of the model, a reward model may be trained based on one or more objectives. The reward model may be employed using a reinforcement learning technique or direct preference optimization technique to further fine-tune the model to bias the slate recommendations in view of the one or more objectives.

Classes IPC  ?

7.

SUGGESTING OBJECT IDENTIFIERS TO INCLUDE IN A COMMUNICATION

      
Numéro d'application 19075460
Statut En instance
Date de dépôt 2025-03-10
Date de la première publication 2025-08-28
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Casey, Hayder
  • Gavini, Naveen
  • Lurie, Daniel Isaac
  • Probasco, Ryan Wilson
  • Steger, Angel
  • Weiner, Jr., Martin Eric

Abrégé

Described are systems and methods that suggest candidate recipients to receive an object identifier from a first user. For example, a first user, independent of a conversation with a second user, may select, close-up, or otherwise view an object identifier. The system, upon detecting the interaction with the object identifier by the first user, may determine one or more second users to suggest to the first user as candidate recipients with which the first user can share the viewed object identifier. The systems and methods may also suggest object identifiers to share with a selected recipient and/or determine two or more users that have a common connection and share an object identifier related to the connection with each of those users.

Classes IPC  ?

  • G06F 16/2453 - Optimisation des requêtes
  • G06F 16/2457 - Traitement des requêtes avec adaptation aux besoins de l’utilisateur
  • G06F 16/907 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
  • G06N 7/01 - Modèles graphiques probabilistes, p. ex. réseaux probabilistes

8.

SYSTEM AND METHODS TO RECOMMEND ITEMS THAT INCREASE LONG-TERM USER SATISFACTION

      
Numéro d'application 18913860
Statut En instance
Date de dépôt 2024-10-11
Date de la première publication 2025-08-14
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Ayed, Mehdi Ben
  • Singh, Vishwakarma

Abrégé

Described are systems and methods that resolve the shortcomings of existing recommendation systems that focus on immediate user reward rather than long-term user satisfaction. The disclosed implementations increase user session duration and user session depth during a session by selecting items that incent the user to remain engaged and participating in the session, rather than optimizing for immediate user metrics.

Classes IPC  ?

  • G06F 16/9535 - Adaptation de la recherche basée sur les profils des utilisateurs et la personnalisation

9.

EXTRACTED IMAGE SEGMENTS COLLAGE

      
Numéro d'application 19196260
Statut En instance
Date de dépôt 2025-05-01
Date de la première publication 2025-08-14
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Temple, David
  • Probasco, Ryan Wilson
  • Farre, Albert Pereta
  • Ramkumar, Steven
  • Mahadev, Rohan
  • Zhao, Luke
  • Kislyuk, Dmitry Olegovich
  • Xue, David Ding-Jia

Abrégé

Described are systems and methods to extract image segments from an image and include those extracted image segments in a collage. The origin information, such as the source image, source image location, etc., from which the extracted image segment is generated is maintained as metadata so that interaction with the extracted image segment on the collage can be used to determine and/or return to the origin of the extracted image segment. Collages may be updated, shared, adjusted, etc., by the creator of the collage or other users.

Classes IPC  ?

  • G06T 11/60 - Édition de figures et de texteCombinaison de figures ou de texte
  • G06Q 30/0601 - Commerce électronique [e-commerce]
  • G06T 7/11 - Découpage basé sur les zones
  • G06V 10/25 - Détermination d’une région d’intérêt [ROI] ou d’un volume d’intérêt [VOI]
  • G06V 10/26 - Segmentation de formes dans le champ d’imageDécoupage ou fusion d’éléments d’image visant à établir la région de motif, p. ex. techniques de regroupementDétection d’occlusion
  • G06V 10/774 - Génération d'ensembles de motifs de formationTraitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source méthodes de Bootstrap, p. ex. "bagging” ou “boosting”
  • G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux

10.

NEURAL TAXONOMY EXPANDER

      
Numéro d'application 19193558
Statut En instance
Date de dépôt 2025-04-29
Date de la première publication 2025-08-14
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Manzoor, Emaad Ahmed
  • Li, Rui
  • Shrouty, Dhananjay
  • Leskovec, Jurij

Abrégé

Systems and methods for automatically placing a taxonomy candidate within an existing taxonomy are presented. More particularly, a neural taxonomy expander (a neural network model) is trained according to the existing, curated taxonomic hierarchy. Moreover, for each node in the taxonomic hierarchy, an embedding vector is generated. A taxonomy candidate is received, where the candidate is to be placed within the existing taxonomy. An embedding vector is generated for the candidate and projected by a projection function of the neural taxonomy expander into the taxonomic hyperspace. A set of closest neighbors to the projected embedding vector of the taxonomy candidate is identified and the closest neighbor of the set is assumed as the parent for the taxonomy candidate. The taxonomy candidate is added to the existing taxonomic hierarchy as a child to the identified parent node.

Classes IPC  ?

  • G06N 5/022 - Ingénierie de la connaissanceAcquisition de la connaissance
  • G06N 3/04 - Architecture, p. ex. topologie d'interconnexion
  • G06N 3/08 - Méthodes d'apprentissage

11.

DYNAMIC FILTER RECOMMENDATIONS

      
Numéro d'application 19048322
Statut En instance
Date de dépôt 2025-02-07
Date de la première publication 2025-06-05
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Agarwal, Navin
  • Hsieh, Judy Yi-Chun
  • Limongan, Debbie Ayano
  • Chen, Lianghao
  • Aggarwal, Amit
  • Bornstein, Julie

Abrégé

A user preference hierarchy is determined from user response to images. Images may be tagged using machine learning models trained to determine values for images. Products are clustered according to product vectors. Images of products within a cluster are clustered according to composition and groups of images are selected from image clusters for soliciting feedback regarding user preference for products of a cluster. Feedback is used to train a user preference model to estimate affinity for a product vector. A user may provide feedback regarding a price point and products are weighted according to a distribution about the price point. The distribution may be asymmetrical according to direction of movement of the price point. Filters may be dynamically defined and presented to a user based on popularity and frequency of occurrence of attribute-value pairs of search results and based on feedback regarding the search results.

Classes IPC  ?

12.

DETERMINING TOPIC COHESION BETWEEN POSTED AND LINKED CONTENT

      
Numéro d'application 19048573
Statut En instance
Date de dépôt 2025-02-07
Date de la première publication 2025-06-05
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Gusev, Andrey Dmitriyevich
  • Zhang, Wenke
  • Chang, Hsiao-Ching
  • Zeng, Qinglong
  • Daoud, Peter John
  • Liu, Jun
  • Chin, Grace
  • Li, Zhuoyuan
  • Hanger, Jacob Franklin
  • Bannister, Vincent

Abrégé

Systems and method for determining a topic cohesion measurement between a content item and a hyperlinked landing page are presented. In one embodiment, a plurality of content item signals is generated for the content item and a corresponding plurality of signals are generated for the hyperlinked landing page. An analysis of the corresponding signals is conducted to determine a measurement of topic cohesion, a topic cohesion score, between the content item and the hyperlinked landing page. A cohesion predictor model is trained to generate the predictive topic cohesion score between an input content item and a hyperlinked landing page. Upon a determination that the topic cohesion score is less than a predetermined threshold, remedial actions are taken regarding the hyperlink of the content item. Alternatively, positive actions may be carried out, including promoting the content item to others, associating advertisements with the content item, and the like.

Classes IPC  ?

  • H04L 51/216 - Gestion de l'historique des conversations, p. ex. regroupement de messages dans des sessions ou des fils de conversation
  • G06N 20/00 - Apprentissage automatique
  • H04L 51/063 - Adaptation du contenu, p. ex. remplacement d'un contenu inapproprié

13.

Neural taxonomy expander

      
Numéro d'application 16592115
Numéro de brevet 12307382
Statut Délivré - en vigueur
Date de dépôt 2019-10-03
Date de la première publication 2025-05-20
Date d'octroi 2025-05-20
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Manzoor, Emaad Ahmed
  • Li, Rui
  • Shrouty, Dhananjay
  • Leskovec, Jurij

Abrégé

Systems and methods for automatically placing a taxonomy candidate within an existing taxonomy are presented. More particularly, a neural taxonomy expander (a neural network model) is trained according to the existing, curated taxonomic hierarchy. Moreover, for each node in the taxonomic hierarchy, an embedding vector is generated. A taxonomy candidate is received, where the candidate is to be placed within the existing taxonomy. An embedding vector is generated for the candidate and projected by a projection function of the neural taxonomy expander into the taxonomic hyperspace. A set of closest neighbors to the projected embedding vector of the taxonomy candidate is identified and the closest neighbor of the set is assumed as the parent for the taxonomy candidate. The taxonomy candidate is added to the existing taxonomic hierarchy as a child to the identified parent node.

Classes IPC  ?

  • G06N 5/022 - Ingénierie de la connaissanceAcquisition de la connaissance
  • G06N 3/04 - Architecture, p. ex. topologie d'interconnexion
  • G06N 3/08 - Méthodes d'apprentissage

14.

IDENTIFYING IMAGE BASED CONTENT ITEMS USING A LARGE LANGUAGE MODEL

      
Numéro d'application 18499984
Statut En instance
Date de dépôt 2023-11-01
Date de la première publication 2025-05-01
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Ordorica De La Torre, Jesus Armando
  • Chang, Alice Jenlin
  • Lee, Dong Hyun
  • Reger, Darren Peter
  • Yun, David
  • Chen, Jessica

Abrégé

Disclosed are systems and methods that process a selection of a plurality of content items through a Large Language Model (“LLM”) and determine, based on that processing, other content items to present or recommend. For example, one or more non-text content item may be processed to generate one or more captions descriptive of the non-text content item(s). The captions may then be processed by a LLM to determine a narrative description of the content items and the narrative description may be used as a text-based query to determine recommended content items.

Classes IPC  ?

  • G06F 40/169 - Annotation, p. ex. données de commentaires ou notes de bas de page
  • G06F 40/40 - Traitement ou traduction du langage naturel

15.

RECOMMENDING CONTENT ITEMS BASED ON A LONG-TERM OBJECTIVE

      
Numéro d'application 18678748
Statut En instance
Date de dépôt 2024-05-30
Date de la première publication 2025-05-01
Propriétaire Pinterest, Inc. (USA)
Inventeur(s) Ordorica De La Torre, Jesus Armando

Abrégé

Described are systems and methods for implementing a recommendation system that is configured and/or optimized to determine recommended content items based on a long-term objective. The exemplary recommendation system may be generated based on a mapping between content items and the long-term objective. The mapping between the content items and the long-term objective may be determined based on mappings utilizing various interim metrics, which may be determined using trained models configured to predict a respective target variable based on respective inputs. The mapping may also be generated using alignment scores and/or a large language model.

Classes IPC  ?

16.

P

      
Numéro de série 99101040
Statut En instance
Date de dépôt 2025-03-24
Propriétaire Pinterest, Inc. ()
Classes de Nice  ?
  • 35 - Publicité; Affaires commerciales
  • 38 - Services de télécommunications
  • 41 - Éducation, divertissements, activités sportives et culturelles
  • 42 - Services scientifiques, technologiques et industriels, recherche et conception
  • 45 - Services juridiques; services de sécurité; services personnels pour individus
  • 09 - Appareils et instruments scientifiques et électriques

Produits et services

Advertising and promotional services; Advertising and marketing services, namely, promoting the goods and services of others; Business data analysis; Business monitoring and consulting services, namely, tracking web sites and applications of others to provide strategy, insight, marketing, sales, operation, product design, particularly specializing in the use of analytic and statistic models for the understanding and predicting of consumers, businesses, and market trends and actions; Marketing services, namely, promoting or advertising the goods and services of others; Promoting the goods and services of others by providing hypertext links to the web sites of others; Electronic commerce services, namely, providing information about products via telecommunication networks for advertising and sales purposes Electronic bulletin board services Organizing and arranging exhibitions for entertainment purposes; Entertainment, namely, a continuing lifestyle and cooking show broadcast over television, internet, and video media; Providing a website featuring non-downloadable photographs Providing online non-downloadable computer software platforms for creating, uploading, bookmarking, viewing, annotating, sharing, and discovering data, information, and media content; Computer services, namely, creating an on-line community for registered users to participate in discussions, get feedback from their peers, form virtual communities, and engage in social networking services in the field of general interest; Providing a website featuring technology that enables users to create, upload, bookmark, view, annotate, share and discover data, information and media content; Providing online non-downloadable computer software platforms for uploading, posting, showing, displaying, tagging, sharing and transmitting messages, comments, multimedia content, photos, pictures, images, text, information, and other user-generated content; Developing and hosting a server on a global computer network for the purpose of facilitating e-commerce via such a server; Providing online non-downloadable computer software platforms for facilitating sharing and discovering information and media content via mobile devices and local and global computer, mobile, cellular, electronic, wireless, and data communications networks Online social networking services; Online social networking services in the field of commentary, comparison, collaboration, consultation, evaluation, advice, discussion, research, notification, reporting, identification, information sharing, indexing, information location, entertainment, pleasure, or general interest Downloadable computer software for allowing users to interact online with information and media content that other users share, and software that allows users to discover, access and share information about, and media content concerning goods, services, and experiences; Downloadable computer software for creating, uploading, bookmarking, viewing, annotating, sharing, and discovering data, information, and media content; Downloadable mobile applications for creating, uploading, bookmarking, viewing, annotating, sharing, and discovering data, information, and media content; Downloadable computer software for facilitating business promotion, namely, connecting social network users with businesses; Downloadable electronic publications in the nature of blogs, photographs, and graphic art in the field of general human interest; Downloadable computer e-commerce software to allow users to perform electronic business transactions via a global computer network

17.

GENERATING CONTENT BASED ON TEXT AND SUPPLEMENTAL INFORMATION

      
Numéro d'application 18459888
Statut En instance
Date de dépôt 2023-09-01
Date de la première publication 2025-03-06
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Xue, David Ding-Jia
  • Tzeng, Eric Shulee
  • Wang, Yu
  • Zhang, Yinan

Abrégé

Described are systems and methods for providing a content generation service that may be configured to generate content, such as digital images and the like, based on both a textual input and supplemental information. The content generation service may include one or more trained machine learning models that may be configured to generate an image based on a textual input and one or more supplemental information input(s). The supplemental information may include, for example, user information, content information, etc. and can provide context, preferences, or any other additional information beyond the textual input that may be used to generate the content. Further, the content generation service and/or the user may be able to assign weights to each of the textual input and the supplemental information input in connection with the generation of the content.

Classes IPC  ?

18.

BODY TYPE CLASSIFICATION OF CONTENT

      
Numéro d'application 18487645
Statut En instance
Date de dépôt 2023-10-16
Date de la première publication 2025-03-06
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Fawaz, Nadia
  • Ta, Anh Tuong
  • Mahadev, Rohan
  • Juneja, Bhawna
  • Silva Do Nascimento Neto, Pedro
  • Khandagale, Sujay
  • Bannerman Hutchful, Kevin

Abrégé

Described are systems and methods to determine body types of individuals represented in content items. The determined body types may be associated with the content items to facilitate indexing, filtering, diversifying, etc. of the content items based on the determined body types. In exemplary implementations, a corpus of content items may be associated with an embedding vector that includes a representation of the content item. The embedding vectors associated with each content item can be provided as inputs to a trained machine learning model, which can process the embedding vectors to determine one or more body types of individuals represented in each content item while eliminating the need for performing image pre-processing prior to determination of the body type(s) presented in the content item.

Classes IPC  ?

  • G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
  • G06F 16/58 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
  • G06T 7/90 - Détermination de caractéristiques de couleur

19.

ASSOCIATING USER-PROVIDED CONTENT ITEMS TO INTEREST NODES

      
Numéro d'application 18931554
Statut En instance
Date de dépôt 2024-10-30
Date de la première publication 2025-02-13
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Li, Chenyi
  • Guo, Yunsong
  • Liu, Yu

Abrégé

System and methods are presented for associating a user-posted content item with an interest node of an interest taxonomy. A corpus of content items and an interest taxonomy are maintained. The interest taxonomy comprises interest nodes organized in a hierarchical organization, each node having a text label descriptive of the interest node. Additionally, the content items of the corpus are associated with one or more interest nodes of the interest taxonomy. Upon receiving a user-posted content item, feature sets of the received content item are generated, these feature sets based on features and/or aspects of the received content item. After generating at least one feature set, the at least one feature set is provided to an interest prediction model that generates candidate interest nodes for the user-posted content item. At least some of the candidate interest nodes are associated with the user-posted content item in the corpus.

Classes IPC  ?

20.

PROBABILISTIC DETERMINATION OF COMPATIBLE CONTENT

      
Numéro d'application 18828628
Statut En instance
Date de dépôt 2024-09-09
Date de la première publication 2024-12-26
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Johnson, Brian
  • Milinovich, John
  • Riedel, Lance Alan
  • Look, Andrew
  • Narasimhan, Mukund
  • Liu, Yu

Abrégé

According to aspects of the disclosed subject matter, a taste graph comprising likely content collection nodes with corresponding likely digital content items is generated through one or more analyses of a corpus of content collections that is maintained by the online content service. As should be understood, this corpus of content collections is comprised of a plurality of curated content collections, with each content collection comprising a plurality of digital content items. With this taste graph available, as a user generates (or in response to a user generating) a content collection of digital content items, reference can be made to the taste graph to identify one or more digital content items that may be added to the content collection, where the one or more digital content items have a probabilistic likelihood of being complimentary and/or compatible with the other digital content items of the content collection.

Classes IPC  ?

  • G06Q 30/0601 - Commerce électronique [e-commerce]
  • G06F 16/957 - Optimisation de la navigation, p. ex. mise en cache ou distillation de contenus
  • G06Q 30/0201 - Modélisation du marchéAnalyse du marchéCollecte de données du marché
  • G06Q 30/0282 - Notation ou évaluation d’opérateurs commerciaux ou de produits
  • G06Q 50/00 - Technologies de l’information et de la communication [TIC] spécialement adaptées à la mise en œuvre des procédés d’affaires d’un secteur particulier d’activité économique, p. ex. aux services d’utilité publique ou au tourisme

21.

DEBIASED TRAINING OF MACHINE LEARNING SYSTEMS

      
Numéro d'application 18335212
Statut En instance
Date de dépôt 2023-06-15
Date de la première publication 2024-12-19
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Xiao, Pingjie
  • Yin, Peifeng

Abrégé

Described are systems and methods for generating a debiased training dataset and training one or more stages of a multi-stage recommendation system and/or service using the debiased training dataset. Rather than generating training datasets from the output data generated by the multi-stage recommendation system and/or data served by later stages of the multi-stage recommendation system, debiased training datasets may be generated from data that was served by the particular stage of the multi-stage recommendation system that is to be trained using the generated debiased training dataset. The debiased training dataset may be generated by generating pseudo-labels for each data record and comparing the generated pseudo-labels against two thresholds to generate a binary classification of the data records.

Classes IPC  ?

22.

Visual search refinement

      
Numéro d'application 18783684
Numéro de brevet 12461980
Statut Délivré - en vigueur
Date de dépôt 2024-07-25
Date de la première publication 2024-11-14
Date d'octroi 2025-11-04
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Wilson, Jason Luke
  • Gavini, Naveen

Abrégé

Described is a system and method for enabling visual search for information. With each selection of a search term, additional search terms are dynamically selected and presented to the user in conjunction with results matching the currently selected search terms. Likewise, a selected search term may be tokenized and a graphical token presented to the user to represent the selected search term.

Classes IPC  ?

  • G06F 16/00 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet
  • G06F 16/9535 - Adaptation de la recherche basée sur les profils des utilisateurs et la personnalisation

23.

DETERMINING TOPICS FOR TAXONOMIES

      
Numéro d'application 18733690
Statut En instance
Date de dépôt 2024-06-04
Date de la première publication 2024-09-26
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Mahabal, Abhijit
  • Huang, Rui

Abrégé

Systems and methods for determining one or more topics that may be associated and/or grounded with a node of a taxonomy to facilitate the creation and/or modification of the taxonomy. The one or more topics can be determined by generating two layers of associations and/or groundings. In a first layer, tokens can be associated and/or grounded in a corpus of queries, and in a second layer, topics can be associated and/or grounded in the tokens. The topics can then be associated with and/or grounded in nodes of a taxonomy which can facilitate access to content items stored and maintained by an online service. Further, in exemplary implementations where the content items include associations and/or mappings to the corpus of queries, the nodes of the taxonomy (which are associated with one or more topics) can be transitively mapped to the content items.

Classes IPC  ?

  • G06F 16/35 - PartitionnementClassement
  • G06F 16/33 - Requêtes
  • G06F 16/36 - Création d’outils sémantiques, p. ex. ontologie ou thésaurus
  • G06F 40/284 - Analyse lexicale, p. ex. segmentation en unités ou cooccurrence

24.

Suggesting object identifiers to include in a communication

      
Numéro d'application 18629870
Numéro de brevet 12248474
Statut Délivré - en vigueur
Date de dépôt 2024-04-08
Date de la première publication 2024-08-01
Date d'octroi 2025-03-11
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Casey, Hayder
  • Gavini, Naveen
  • Lurie, Daniel Isaac
  • Probasco, Ryan Wilson
  • Steger, Angel
  • Weiner, Jr., Martin Eric

Abrégé

Described are systems and methods that suggest candidate recipients to receive an object identifier from a first user. For example, a first user, independent of a conversation with a second user, may select, close-up, or otherwise view an object identifier. The system, upon detecting the interaction with the object identifier by the first user, may determine one or more second users to suggest to the first user as candidate recipients with which the first user can share the viewed object identifier. The systems and methods may also suggest object identifiers to share with a selected recipient and/or determine two or more users that have a common connection and share an object identifier related to the connection with each of those users.

Classes IPC  ?

  • G06F 16/245 - Traitement des requêtes
  • G06F 16/2453 - Optimisation des requêtes
  • G06F 16/2457 - Traitement des requêtes avec adaptation aux besoins de l’utilisateur
  • G06F 16/907 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
  • G06N 7/01 - Modèles graphiques probabilistes, p. ex. réseaux probabilistes

25.

RECOMMENDATION CAMPAIGNS BASED ON PREDICTED SHORT-TERM USER BEHAVIOR AND PREDICTED LONG-TERM USER BEHAVIOR

      
Numéro d'application 18626137
Statut En instance
Date de dépôt 2024-04-03
Date de la première publication 2024-07-25
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Zhao, Bo
  • Egan, John William Gupta
  • Orten, Burkay Birant
  • Narita, Koichiro
  • Weisfeld-Filson, Samuel Seth

Abrégé

Described are systems and methods for generating recommendation campaigns that optimize for both a desired short-term user behavior and a desired long-term user behavior. In comparison to existing techniques that focus on targeting advertisements or recommendations to specific individuals with a single goal of receiving an interaction with the advertisement from that individual (i.e., a desired short-term behavior), the disclosed implementations consider the long-term user behavior, such as increased visits to a website during a long-term rage, and generate a recommendation campaign that also optimizes for that desired long-term user behavior.

Classes IPC  ?

26.

INTELLIGENT VIDEO PLAYBACK

      
Numéro d'application 18605366
Statut En instance
Date de dépôt 2024-03-14
Date de la première publication 2024-07-04
Propriétaire Pinterest, Inc. (USA)
Inventeur(s) Ma, Liang

Abrégé

Described are systems and methods for determining and/or generating a queue of content items to improve the playback experience of the content items for a user. The content items may be obtained by a client device from an online service in response to a query, a request for content items, etc. Relevance rankings and/or scores associated with the content items may be replaced and/or augmented with a playability score, which can represent a quality of the playback experience associated with the content item. The playability score may be aggregated with the relevance and/or user engagement score to determine an overall playback score for each content item. The content items may be ranked, ordered, arranged, and/or presented in accordance with the overall playback scores associated with the content items to facilitate an improved playback experience for a user associated with the client device.

Classes IPC  ?

  • H04N 21/232 - Opération de récupération de contenu au sein d'un serveur, p. ex. lecture de flux vidéo du réseau de disques
  • H04N 21/2387 - Traitement de flux en réponse à une requête de reproduction par un utilisateur final, p. ex. pour la lecture à vitesse variable ("trick play")
  • H04N 21/25 - Opérations de gestion réalisées par le serveur pour faciliter la distribution de contenu ou administrer des données liées aux utilisateurs finaux ou aux dispositifs clients, p. ex. authentification des utilisateurs finaux ou des dispositifs clients ou apprentissage des préférences des utilisateurs pour recommander des films
  • H04N 21/472 - Interface pour utilisateurs finaux pour la requête de contenu, de données additionnelles ou de servicesInterface pour utilisateurs finaux pour l'interaction avec le contenu, p. ex. pour la réservation de contenu ou la mise en place de rappels, pour la requête de notification d'événement ou pour la transformation de contenus affichés

27.

EMBEDDING INFERENCE

      
Numéro d'application 18595166
Statut En instance
Date de dépôt 2024-03-04
Date de la première publication 2024-06-27
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Vinicombe, Heath
  • Li, Chenyi
  • Guo, Yunsong
  • Liu, Yu

Abrégé

Systems and methods are presented for inferring an embedding vector of an item of a first type into the embedding space. Upon receiving a first time for which there is no embedding vector, documents of a document corpus that include (co-occurrence) both the received item and other items of the same type are identified. Of those other items that have embedding vectors, those embedding vectors are retrieved and averaged. The resulting averaged embedding vector is established as an inferred embedding vector for the received item.

Classes IPC  ?

  • G06F 40/30 - Analyse sémantique
  • G06N 7/00 - Agencements informatiques fondés sur des modèles mathématiques spécifiques

28.

Recommendation campaigns based on predicted short-term user behavior and predicted long-term user behavior

      
Numéro d'application 15612851
Numéro de brevet 11983735
Statut Délivré - en vigueur
Date de dépôt 2017-06-02
Date de la première publication 2024-05-14
Date d'octroi 2024-05-14
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Zhao, Bo
  • Egan, John William Gupta
  • Orten, Burkay Birant
  • Narita, Koichiro
  • Weisfeld-Filson, Samuel Seth

Abrégé

Described are systems and methods for generating recommendation campaigns that optimize for both a desired short-term user behavior and a desired long-term user behavior. In comparison to existing techniques that focus on targeting advertisements or recommendations to specific individuals with a single goal of receiving an interaction with the advertisement from that individual (i.e., a desired short-term behavior), the disclosed implementations consider the long-term user behavior, such as increased visits to a website during a long-term rage, and generate a recommendation campaign that also optimizes for that desired long-term user behavior.

Classes IPC  ?

29.

AGGREGATED EMBEDDINGS FOR A CORPUS GRAPH

      
Numéro d'application 18414195
Statut En instance
Date de dépôt 2024-01-16
Date de la première publication 2024-05-09
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Leskovec, Jurij
  • Eksombatchai, Chantat
  • Chen, Kaifeng
  • He, Ruining
  • Ying, Rex

Abrégé

Systems and methods for generating embeddings for nodes of a corpus graph are presented. More particularly, operations for generation of an aggregated embedding vector for a target node is efficiently divided among operations on a central processing unit and operations on a graphic processing unit. With regard to a target node within a corpus graph, processing by one or more central processing units (CPUs) is conducted to identify the target node's relevant neighborhood (of nodes) within the corpus graph. This information is prepared and passed to one or more graphic processing units (GPUs) that determines the aggregated embedding vector for the target node according to data of the relevant neighborhood of the target node.

Classes IPC  ?

  • G06N 3/08 - Méthodes d'apprentissage
  • G06F 16/182 - Systèmes de fichiers distribués
  • G06F 16/22 - IndexationStructures de données à cet effetStructures de stockage
  • G06F 16/51 - IndexationStructures de données à cet effetStructures de stockage
  • G06F 16/901 - IndexationStructures de données à cet effetStructures de stockage
  • G06F 16/9035 - Filtrage basé sur des données supplémentaires, p. ex. sur des profils d'utilisateurs ou de groupes
  • G06F 16/906 - GroupementClassement
  • G06F 16/9535 - Adaptation de la recherche basée sur les profils des utilisateurs et la personnalisation
  • G06F 16/9536 - Personnalisation de la recherche basée sur le filtrage social ou collaboratif
  • G06F 18/211 - Sélection du sous-ensemble de caractéristiques le plus significatif
  • G06F 18/214 - Génération de motifs d'entraînementProcédés de Bootstrapping, p. ex. ”bagging” ou ”boosting”
  • G06F 18/2413 - Techniques de classification relatives au modèle de classification, p. ex. approches paramétriques ou non paramétriques basées sur les distances des motifs d'entraînement ou de référence
  • G06N 3/04 - Architecture, p. ex. topologie d'interconnexion
  • G06N 20/00 - Apprentissage automatique
  • G06V 30/196 - Reconnaissance utilisant des moyens électroniques utilisant des comparaisons successives des signaux d’images avec plusieurs références

30.

OPTIMAL NOTIFICATION

      
Numéro d'application 18403457
Statut En instance
Date de dépôt 2024-01-03
Date de la première publication 2024-04-25
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Zhao, Bo
  • Weisfeld-Filson, Samuel Seth
  • Egan, John William Gupta
  • Orten, Burkay Birant
  • Narita, Koichiro

Abrégé

Systems and methods for generating user notifications to a set of users of a social networking service is presented. For each user of a set of users of the social networking service, one or more machine learning models selects an optimal notification channel, an optimal notification template, and optimal personalization content for configurable elements of a selected notification template. Each of these determinations/selections is made according to and based on a likelihood of increased user engagement with the social networking service. Upon determining the notification channel, notification template, and personalizations to the template, the notification is generated and sent to the corresponding user.

Classes IPC  ?

  • G06Q 50/00 - Technologies de l’information et de la communication [TIC] spécialement adaptées à la mise en œuvre des procédés d’affaires d’un secteur particulier d’activité économique, p. ex. aux services d’utilité publique ou au tourisme

31.

Order management systems and methods

      
Numéro d'application 18394192
Numéro de brevet 12387251
Statut Délivré - en vigueur
Date de dépôt 2023-12-22
Date de la première publication 2024-04-18
Date d'octroi 2025-08-12
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Rodriguez, Jorge
  • Zhou, Xinyi
  • Grunewald, James
  • Aggarwal, Amit
  • Zaytsev, Andrey
  • Gilfanov, Ruslan

Abrégé

Example order management systems and methods are described. In one implementation, a catalog ingestion system receives data associated with multiple products offered by multiple brands. A commerce management system receives a customer order from a customer. The customer order includes at least a portion of the multiple products offered by the multiple brands. The commerce management system splits the customer order into multiple brand orders such that each brand order is associated with products in the customer order from a particular brand. An integration platform fulfills the brand orders by submitting the brand orders to the associated brands.

Classes IPC  ?

  • G06Q 30/06 - Transactions d’achat, de vente ou de crédit-bail
  • G06F 9/445 - Chargement ou démarrage de programme
  • G06Q 10/083 - Expédition
  • G06Q 10/0833 - Repérage
  • G06Q 10/0837 - Transactions de retour
  • G06Q 10/087 - Gestion d’inventaires ou de stocks, p. ex. exécution des commandes, approvisionnement ou régularisation par rapport aux commandes
  • G06Q 10/107 - Gestion informatisée du courrier électronique
  • G06Q 20/08 - Architectures de paiement
  • G06Q 30/0601 - Commerce électronique [e-commerce]
  • H04L 51/42 - Aspects liés aux boîtes aux lettres, p. ex. synchronisation des boîtes aux lettres
  • H04L 101/37 - Adresses courriel

32.

Identifying content items in response to a text-based request

      
Numéro d'application 18500791
Numéro de brevet 12353471
Statut Délivré - en vigueur
Date de dépôt 2023-11-02
Date de la première publication 2024-02-22
Date d'octroi 2025-07-08
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Pancha, Nikil
  • Zhai, Andrew Huan
  • Rosenberg, Charles Joseph

Abrégé

Systems and methods for responding to a subscriber's text-based request for content items are presented. In response to a request from a subscriber, word pieces are generated from the text-based terms of the request. A request embedding vector of the word pieces is obtained from a trained machine learning model. Using the request embedding vector, a set of content items, from a corpus of content items, is identified. At least some content items of the set of content items are returned to the subscriber in response to the text-based request for content items.

Classes IPC  ?

  • G06F 16/483 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des métadonnées provenant automatiquement du contenu
  • G06F 16/44 - NavigationVisualisation à cet effet
  • G06F 16/45 - GroupementClassement
  • G06F 40/56 - Génération de langage naturel
  • G06N 20/00 - Apprentissage automatique

33.

Hair pattern determination and filtering

      
Numéro d'application 18484186
Numéro de brevet 12174881
Statut Délivré - en vigueur
Date de dépôt 2023-10-10
Date de la première publication 2024-02-01
Date d'octroi 2024-12-24
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Fawaz, Nadia
  • Ta, Anh Tuong
  • Juneja, Bhawna
  • Mahadev, Rohan
  • Moy, Valerie
  • Kislyuk, Dmitry Olegovich
  • Xue, David Ding-Jia
  • Schaefbauer, Christopher Lee
  • Roth, Graham
  • Yau, William
  • Disanto, Jordan
  • Zhang, Ding
  • Voiss, David

Abrégé

Described are systems and methods to determine hair patterns presented in content items. The determined hair patterns may be associated with the content items to facilitate indexing, filtering, etc. of the content items based on the determined hair patterns. In exemplary implementations, a corpus of content items may be associated with an embedding vector that includes a binary representation of the content item. The embedding vectors associated with each content item can be provided as inputs to a trained machine learning model, which can process the embedding vectors to determine one or more hair patterns presented in each content item while eliminating the need for performing image pre-processing prior to determination of the hair pattern(s) presented in the content item.

Classes IPC  ?

  • G06F 16/532 - Formulation de requêtes, p. ex. de requêtes graphiques
  • G06F 16/538 - Présentation des résultats des requêtes

34.

DETERMINING LINKED SPAM CONTENT

      
Numéro d'application 17866367
Statut En instance
Date de dépôt 2022-07-15
Date de la première publication 2024-01-18
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Singh, Vishwakarma
  • Song, Yuanfang

Abrégé

Systems and methods for determining whether a linked content page may include spamming, malicious, and/or otherwise undesirable content. The linked content page may be crawled, scraped, and/or parsed to extract various information associated with the text, media items, and/or structure of the linked content page. The text, media, and/or structure information may be analyzed and processed to generate one or more textual features, media features, and/or structural features, which may then be processed by a trained machine learning model to determine whether the content page includes spamming, malicious, and/or otherwise undesirable content.

Classes IPC  ?

  • G06F 40/284 - Analyse lexicale, p. ex. segmentation en unités ou cooccurrence
  • G06F 16/93 - Systèmes de gestion de documents
  • G06F 21/55 - Détection d’intrusion locale ou mise en œuvre de contre-mesures

35.

Content presentation

      
Numéro d'application 18467129
Numéro de brevet 12282521
Statut Délivré - en vigueur
Date de dépôt 2023-09-14
Date de la première publication 2024-01-04
Date d'octroi 2025-04-22
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Lu, Wendy
  • Velo, Justin
  • Tow, Kelvin
  • You, Mengya
  • Crawford, Nicole
  • He, Harrison

Abrégé

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing content. One of the methods includes providing a plurality of image content items to an application interface of a client device for presentation; receiving a user selection of a particular image content item of the plurality of presented image content items; and responsive to the selection, providing a combination of native content and third party content associated with the selected image content item, wherein the native content includes a close up view of the selected image content item and the third party content includes a third party webpage.

Classes IPC  ?

  • G06F 17/00 - Équipement ou méthodes de traitement de données ou de calcul numérique, spécialement adaptés à des fonctions spécifiques
  • G06F 3/04845 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs pour la transformation d’images, p. ex. glissement, rotation, agrandissement ou changement de couleur
  • G06F 3/0485 - Défilement ou défilement panoramique
  • G06F 16/54 - NavigationVisualisation à cet effet
  • G06F 16/954 - Navigation, p. ex. en utilisant la navigation par catégories
  • G06F 16/957 - Optimisation de la navigation, p. ex. mise en cache ou distillation de contenus

36.

Determining topics for taxonomies

      
Numéro d'application 17844640
Numéro de brevet 12038961
Statut Délivré - en vigueur
Date de dépôt 2022-06-20
Date de la première publication 2023-12-21
Date d'octroi 2024-07-16
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Mahabal, Abhijit
  • Huang, Rui

Abrégé

Systems and methods for determining one or more topics that may be associated and/or grounded with a node of a taxonomy to facilitate the creation and/or modification of the taxonomy. The one or more topics can be determined by generating two layers of associations and/or groundings. In a first layer, tokens can be associated and/or grounded in a corpus of queries, and in a second layer, topics can be associated and/or grounded in the tokens. The topics can then be associated with and/or grounded in nodes of a taxonomy which can facilitate access to content items stored and maintained by an online service. Further, in exemplary implementations where the content items include associations and/or mappings to the corpus of queries, the nodes of the taxonomy (which are associated with one or more topics) can be transitively mapped to the content items.

Classes IPC  ?

  • G06F 16/35 - PartitionnementClassement
  • G06F 16/33 - Requêtes
  • G06F 16/36 - Création d’outils sémantiques, p. ex. ontologie ou thésaurus
  • G06F 40/284 - Analyse lexicale, p. ex. segmentation en unités ou cooccurrence

37.

Determining topic cohesion between posted and linked content

      
Numéro d'application 18302741
Numéro de brevet 12244554
Statut Délivré - en vigueur
Date de dépôt 2023-04-18
Date de la première publication 2023-11-30
Date d'octroi 2025-03-04
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Gusev, Andrey Dmitriyevich
  • Zhang, Wenke
  • Chang, Hsiao-Ching
  • Zeng, Qinglong
  • Daoud, Peter John
  • Liu, Jun
  • Chin, Grace
  • Li, Zhuoyuan
  • Hanger, Jacob Franklin
  • Bannister, Vincent

Abrégé

Systems and method for determining a topic cohesion measurement between a content item and a hyperlinked landing page are presented. In one embodiment, a plurality of content item signals is generated for the content item and a corresponding plurality of signals are generated for the hyperlinked landing page. An analysis of the corresponding signals is conducted to determine a measurement of topic cohesion, a topic cohesion score, between the content item and the hyperlinked landing page. A cohesion predictor model is trained to generate the predictive topic cohesion score between an input content item and a hyperlinked landing page. Upon a determination that the topic cohesion score is less than a predetermined threshold, remedial actions are taken regarding the hyperlink of the content item. Alternatively, positive actions may be carried out, including promoting the content item to others, associating advertisements with the content item, and the like.

Classes IPC  ?

  • H04L 51/216 - Gestion de l'historique des conversations, p. ex. regroupement de messages dans des sessions ou des fils de conversation
  • G06N 20/00 - Apprentissage automatique
  • H04L 51/063 - Adaptation du contenu, p. ex. remplacement d'un contenu inapproprié

38.

Node graph pruning and fresh content

      
Numéro d'application 18364998
Numéro de brevet 12277175
Statut Délivré - en vigueur
Date de dépôt 2023-08-03
Date de la première publication 2023-11-30
Date d'octroi 2025-04-15
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Eksombatchai, Chantat
  • Leskovec, Jurij
  • Sharma, Rahul
  • Sugnet, Charles Walsh
  • Ulrich, Mark Bormann

Abrégé

This disclosure describes systems and methods that facilitate the generation of recommendations by traversing a graph. Walks that traverse the graph may be initiated from a plurality of different nodes in the node graph. In order to give greater or lesser weight to particular nodes, the walks may have different lengths depending on the nodes from which they are initiated, or an unequal amount of walks may be distributed between nodes from which walks are initiated. A plurality of walks through a node graph may be tracked, and visit counts or scores for nodes in the node graph may be determined. For example, scores may be increased for nodes that are visited by a walk initiated from a first node and a second walk initiated from a second node, or scores may be decreased for nodes that are not visited by a first walk initiated from a first node and a second walk initiated from a second node. Content corresponding to nodes may be recommended based on the scores or visit counts.

Classes IPC  ?

  • G06F 7/00 - Procédés ou dispositions pour le traitement de données en agissant sur l'ordre ou le contenu des données maniées
  • G06F 16/2457 - Traitement des requêtes avec adaptation aux besoins de l’utilisateur
  • G06F 16/435 - Filtrage basé sur des données supplémentaires, p. ex. sur des profils d'utilisateurs ou de groupes
  • G06F 16/901 - IndexationStructures de données à cet effetStructures de stockage
  • G06F 16/958 - Organisation ou gestion de contenu de sites Web, p. ex. publication, conservation de pages ou liens automatiques
  • G06F 18/23 - Techniques de partitionnement
  • G06Q 30/0201 - Modélisation du marchéAnalyse du marchéCollecte de données du marché
  • G06F 16/487 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des informations géographiques ou spatiales, p. ex. la localisation

39.

Skin tone filter

      
Numéro d'application 18361481
Numéro de brevet 12169519
Statut Délivré - en vigueur
Date de dépôt 2023-07-28
Date de la première publication 2023-11-23
Date d'octroi 2024-12-17
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Daya, Rahim
  • Bhasin, Laksh
  • Wang, Xixia
  • Rogers, Stephanie
  • Williams, Candace
  • Kuchimpos, Ricardo
  • Morgan, Candice
  • Brown, Larkin

Abrégé

Methods, systems, and apparatus, including computer programs encoded on computer storage media for receiving a set of images at a social media system, wherein each image includes one or more recognized features associated with one or more lightness values; indexing each image using the one or more recognized features and the associated range of lightness values; receiving a query; determining a first group of images that is responsive to the query; determining that the query triggers a lightness filter to be displayed on the user device; providing the first group of images for display on a user interface with one or more lightness filter indicators; and in response to a user selection of one of the one or more lightness filter indicators: filtering the first group of images to determine a filtered group of images, and updating the images provided for display according to the filtered group of images.

Classes IPC  ?

  • G06T 7/40 - Analyse de la texture
  • G06F 16/51 - IndexationStructures de données à cet effetStructures de stockage
  • G06F 16/535 - Filtrage basé sur des données supplémentaires, p. ex. sur des profils d'utilisateurs ou de groupes
  • G06V 40/10 - Corps d’êtres humains ou d’animaux, p. ex. occupants de véhicules automobiles ou piétonsParties du corps, p. ex. mains

40.

Intelligent video playback

      
Numéro d'application 17729866
Numéro de brevet 11968409
Statut Délivré - en vigueur
Date de dépôt 2022-04-26
Date de la première publication 2023-10-26
Date d'octroi 2024-04-23
Propriétaire Pinterest, Inc. (USA)
Inventeur(s) Ma, Liang

Abrégé

Described are systems and methods for determining and/or generating a queue of content items to improve the playback experience of the content items for a user. The content items may be obtained, for example, by a client device from an online service in response to a query, a request for content items, and the like. Relevance rankings and/or scores associated with the content items may be replaced and/or augmented with a playability score, which can represent a quality of the playback experience associated with each content item. The playability score for each content item may be aggregated with the relevance and/or user engagement score associated with each content item to determine an overall playback score for each content item. The content items may be ranked, ordered, arranged, and/or presented in accordance with the overall playback scores associated with the content items to facilitate an improved playback experience for a user associated with the client device.

Classes IPC  ?

  • H04N 21/232 - Opération de récupération de contenu au sein d'un serveur, p. ex. lecture de flux vidéo du réseau de disques
  • H04N 21/2387 - Traitement de flux en réponse à une requête de reproduction par un utilisateur final, p. ex. pour la lecture à vitesse variable ("trick play")
  • H04N 21/25 - Opérations de gestion réalisées par le serveur pour faciliter la distribution de contenu ou administrer des données liées aux utilisateurs finaux ou aux dispositifs clients, p. ex. authentification des utilisateurs finaux ou des dispositifs clients ou apprentissage des préférences des utilisateurs pour recommander des films
  • H04N 21/472 - Interface pour utilisateurs finaux pour la requête de contenu, de données additionnelles ou de servicesInterface pour utilisateurs finaux pour l'interaction avec le contenu, p. ex. pour la réservation de contenu ou la mise en place de rappels, pour la requête de notification d'événement ou pour la transformation de contenus affichés

41.

Visual object graphs

      
Numéro d'application 18344397
Numéro de brevet 12443651
Statut Délivré - en vigueur
Date de dépôt 2023-06-29
Date de la première publication 2023-10-26
Date d'octroi 2025-10-14
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Kim, Eric
  • Kislyuk, Dmitry Olegovich

Abrégé

Disclosed are implementations that enable the linking or connection of objects and different scenes in which those objects are represented. For example, a corpus of scenes (e.g., digital images) that include a representation of one or more objects may be processed using the disclosed implementations to segment from those scenes the individual objects represented in those scenes. The disclosed implementations may further determine clusters of visually similar object segments and form object clusters for those object segments. The scenes that include those object segments are also linked to the object cluster. With scenes linked to different object clusters, a user may select one or more query objects or a query scene and be presented with other scenes that include visually similar objects, even though the overall scenes may be visually different.

Classes IPC  ?

  • G06F 16/55 - GroupementClassement
  • G06F 17/16 - Calcul de matrice ou de vecteur
  • G06F 18/22 - Critères d'appariement, p. ex. mesures de proximité
  • G06F 18/23 - Techniques de partitionnement
  • G06T 7/10 - DécoupageDétection de bords
  • G06V 20/30 - ScènesÉléments spécifiques à la scène dans les albums, les collections ou les contenus partagés, p. ex. des photos ou des vidéos issus des réseaux sociaux

42.

Dynamic filter recommendations

      
Numéro d'application 18341589
Numéro de brevet 12242488
Statut Délivré - en vigueur
Date de dépôt 2023-06-26
Date de la première publication 2023-10-26
Date d'octroi 2025-03-04
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Agarwal, Navin
  • Hsieh, Judy Yi-Chun
  • Limongan, Debbie Ayano
  • Chen, Lianghao
  • Aggarwal, Amit
  • Bornstein, Julie

Abrégé

A user preference hierarchy is determined from user response to images. Images may be tagged using machine learning models trained to determine values for images. Products are clustered according to product vectors. Images of products within a cluster are clustered according to composition and groups of images are selected from image clusters for soliciting feedback regarding user preference for products of a cluster. Feedback is used to train a user preference model to estimate affinity for a product vector. A user may provide feedback regarding a price point and products are weighted according to a distribution about the price point. The distribution may be asymmetrical according to direction of movement of the price point. Filters may be dynamically defined and presented to a user based on popularity and frequency of occurrence of attribute-value pairs of search results and based on feedback regarding the search results.

Classes IPC  ?

  • G06F 16/20 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet de données structurées, p. ex. de données relationnelles
  • G06F 16/2457 - Traitement des requêtes avec adaptation aux besoins de l’utilisateur
  • G06N 20/00 - Apprentissage automatique
  • G06Q 30/0601 - Commerce électronique [e-commerce]
  • H04L 67/50 - Services réseau
  • G06N 3/08 - Méthodes d'apprentissage

43.

Determining emebedding vectors for an unmapped content item using embedding inferenece

      
Numéro d'application 16568932
Numéro de brevet 11797775
Statut Délivré - en vigueur
Date de dépôt 2019-09-12
Date de la première publication 2023-10-24
Date d'octroi 2023-10-24
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Vinicombe, Heath
  • Li, Chenyi
  • Guo, Yunsong
  • Liu, Yu

Abrégé

Systems and methods are presented for inferring an embedding vector of an item of a first type into the embedding space. Upon receiving a first time for which there is no embedding vector, documents of a document corpus that include (co-occurrence) both the received item and other items of the same type are identified. Of those other items that have embedding vectors, those embedding vectors are retrieved and averaged. The resulting averaged embedding vector is established as an inferred embedding vector for the received item.

Classes IPC  ?

  • G06F 40/30 - Analyse sémantique
  • G06N 7/00 - Agencements informatiques fondés sur des modèles mathématiques spécifiques

44.

Visual search refinement

      
Numéro d'application 18332361
Numéro de brevet 12072945
Statut Délivré - en vigueur
Date de dépôt 2023-06-09
Date de la première publication 2023-10-12
Date d'octroi 2024-08-27
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Wilson, Jason Luke
  • Gavini, Naveen

Abrégé

Described is a system and method for enabling visual search for information. With each selection of a search term, additional search terms are dynamically selected and presented to the user in conjunction with results matching the currently selected search terms. Likewise, a selected search term may be tokenized and a graphical token presented to the user to represent the selected search term.

Classes IPC  ?

  • G06F 16/00 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet
  • G06F 16/9535 - Adaptation de la recherche basée sur les profils des utilisateurs et la personnalisation

45.

Hair pattern determination and filtering

      
Numéro d'application 17710451
Numéro de brevet 11816144
Statut Délivré - en vigueur
Date de dépôt 2022-03-31
Date de la première publication 2023-10-05
Date d'octroi 2023-11-14
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Fawaz, Nadia
  • Ta, Anh Tuong
  • Juneja, Bhawna
  • Mahadev, Rohan
  • Moy, Valerie
  • Kislyuk, Dmitry Olegovich
  • Xue, David Ding-Jia
  • Schaefbauer, Christopher Lee
  • Roth, Graham
  • Yau, William
  • Disanto, Jordan
  • Zhang, Ding
  • Voiss, David

Abrégé

Described are systems and methods to determine hair patterns presented in content items. The determined hair patterns may be associated with the content items to facilitate indexing, filtering, etc. of the content items based on the determined hair patterns. In exemplary implementations, a corpus of content items may be associated with an embedding vector that includes a binary representation of the content item. The embedding vectors associated with each content item can be provided as inputs to a trained machine learning model, which can process the embedding vectors to determine one or more hair patterns presented in each content item while eliminating the need for performing image pre-processing prior to determination of the hair pattern(s) presented in the content item.

Classes IPC  ?

46.

PROMOTING REPRESENTATIONS OF ITEMS TO USERS ON BEHALF OF SELLERS OF THOSE ITEMS

      
Numéro d'application 18324048
Statut En instance
Date de dépôt 2023-05-25
Date de la première publication 2023-09-21
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Kendall, Timothy Alan
  • Fumarola, Francis Joseph
  • Malhotra, Nipoon

Abrégé

This disclosure describes systems and methods for establishing promotions for sellers and promoting images of items to users on behalf of sellers. A management service receives a source location identifier from a seller, processes images stored in an image data store to determine images that include the source location identifier in the corresponding image information and includes those images in a promotion that is established for the seller. Likewise, the management service may determine users that have previously interacted with the images and include those users in the promotion campaign.

Classes IPC  ?

47.

Lightness filter

      
Numéro d'application 17145823
Numéro de brevet 11762899
Statut Délivré - en vigueur
Date de dépôt 2021-01-11
Date de la première publication 2023-09-19
Date d'octroi 2023-09-19
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Daya, Rahim
  • Bhasin, Laksh
  • Wang, Xixia
  • Rogers, Stephanie
  • Williams, Candace
  • Kuchimpos, Ricardo
  • Morgan, Candice
  • Brown, Larkin

Abrégé

Methods, systems and apparatus, including computer programs encoded on computer storage media for receiving a set of images at a social media system, wherein each image includes one or more recognized features associated with one or more lightness values; indexing each image using the one or more recognized features and the associated range of lightness values; receiving a query; determining a first group of images that is responsive to the query; determining that the query triggers a lightness filter to be displayed on the user device; providing the first group of images for display on a user interface with one or more lightness filter indicators; and in response to a user selection of one of the one or more lightness filter indicators: filtering the first group of images to determine a filtered group of images, and updating the images provided for display according to the filtered group of images.

Classes IPC  ?

  • G06T 7/40 - Analyse de la texture
  • G06F 16/51 - IndexationStructures de données à cet effetStructures de stockage
  • G06F 16/535 - Filtrage basé sur des données supplémentaires, p. ex. sur des profils d'utilisateurs ou de groupes
  • G06V 40/10 - Corps d’êtres humains ou d’animaux, p. ex. occupants de véhicules automobiles ou piétonsParties du corps, p. ex. mains

48.

Node graph pruning and fresh content

      
Numéro d'application 17003851
Numéro de brevet 11762908
Statut Délivré - en vigueur
Date de dépôt 2020-08-26
Date de la première publication 2023-09-19
Date d'octroi 2023-09-19
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Eksombatchai, Chantat
  • Leskovec, Jurij
  • Sharma, Rahul
  • Sugnet, Charles Walsh
  • Ulrich, Mark Bormann

Abrégé

This disclosure describes systems and methods that facilitate the generation of recommendations by traversing a graph. Walks that traverse the graph may be initiated from a plurality of different nodes in the node graph. In order to give greater or lesser weight to particular nodes, the walks may have different lengths depending on the nodes from which they are initiated, or an unequal amount of walks may be distributed between nodes from which walks are initiated. A plurality of walks through a node graph may be tracked, and visit counts or scores for nodes in the node graph may be determined. For example, scores may be increased for nodes that are visited by a walk initiated from a first node and a second walk initiated from a second node, or scores may be decreased for nodes that are not visited by a first walk initiated from a first node and a second walk initiated from a second node. Content corresponding to nodes may be recommended based on the scores or visit counts.

Classes IPC  ?

  • G06F 7/00 - Procédés ou dispositions pour le traitement de données en agissant sur l'ordre ou le contenu des données maniées
  • G06F 16/901 - IndexationStructures de données à cet effetStructures de stockage
  • G06Q 30/0201 - Modélisation du marchéAnalyse du marchéCollecte de données du marché
  • G06F 16/2457 - Traitement des requêtes avec adaptation aux besoins de l’utilisateur
  • G06F 16/435 - Filtrage basé sur des données supplémentaires, p. ex. sur des profils d'utilisateurs ou de groupes
  • G06F 16/487 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des informations géographiques ou spatiales, p. ex. la localisation

49.

Methods of and systems for searching by incorporating user-entered information

      
Numéro d'application 18318597
Numéro de brevet 11977554
Statut Délivré - en vigueur
Date de dépôt 2023-05-16
Date de la première publication 2023-09-14
Date d'octroi 2024-05-07
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Tanne, Michael
  • Lu, Yunshan
  • Karsh, Bruce D.

Abrégé

A system for and a method of using user-entered information to return more meaningful information in response to Internet search queries are disclosed. A method in accordance with the disclosed subject matter comprises managing a database in response to multiple user inputs and displaying search results from the database in response to a search query. The search results include a results list and supplemental data related to the search query. Managing the database includes, among other things, re-ranking elements in the results list, storing information related to relevancies of elements in the results list, blocking a link in the results list, storing links to documents related to the search query, or any combination of these. The supplemental data include descriptions of or indices to one or more concepts related to the search query.

Classes IPC  ?

  • G06F 16/00 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet
  • G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p. ex. des menus
  • G06F 16/2457 - Traitement des requêtes avec adaptation aux besoins de l’utilisateur
  • G06F 16/332 - Formulation de requêtes
  • G06F 16/951 - IndexationTechniques d’exploration du Web
  • G06F 16/9535 - Adaptation de la recherche basée sur les profils des utilisateurs et la personnalisation
  • G06F 16/9538 - Présentation des résultats des requêtes
  • G06F 40/134 - Création de liens hypertexte

50.

Embedding inference

      
Numéro d'application 18315426
Numéro de brevet 11960846
Statut Délivré - en vigueur
Date de dépôt 2023-05-10
Date de la première publication 2023-09-07
Date d'octroi 2024-04-16
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Vinicombe, Heath
  • Li, Chenyi
  • Guo, Yunsong
  • Liu, Yu

Abrégé

Systems and methods are presented for inferring an embedding vector of an item of a first type into the embedding space. Upon receiving a first time for which there is no embedding vector, documents of a document corpus that include (co-occurrence) both the received item and other items of the same type are identified. Of those other items that have embedding vectors, those embedding vectors are retrieved and averaged. The resulting averaged embedding vector is established as an inferred embedding vector for the received item.

Classes IPC  ?

  • G06F 40/30 - Analyse sémantique
  • G06N 7/00 - Agencements informatiques fondés sur des modèles mathématiques spécifiques

51.

CONTEXT BASED ADVERTISEMENT PREDICTION

      
Numéro d'application 17673613
Statut En instance
Date de dépôt 2022-02-16
Date de la première publication 2023-08-17
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Zhang, Jinyin
  • Chen, Liangzhe
  • Xu, Jiajing

Abrégé

Described are systems and methods to determine advertisements to be presented to a user. To determine the advertisements to be presented to the user, the described systems and methods utilize localized contextual information to select the advertisements and the relative positioning of the advertisements to be presented, so as to select and present more relevant advertisements based on the content that is surrounding and proximate to the presentation of the selected advertisements.

Classes IPC  ?

  • G06Q 30/02 - MarketingEstimation ou détermination des prixCollecte de fonds
  • G06N 3/04 - Architecture, p. ex. topologie d'interconnexion
  • G06N 3/08 - Méthodes d'apprentissage

52.

SEQUENTIAL MODEL FOR DETERMINING USER REPRESENTATIONS

      
Numéro d'application 18166415
Statut En instance
Date de dépôt 2023-02-08
Date de la première publication 2023-08-10
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Zhai, Andrew Huan
  • Pancha, Nikil
  • Chen, Haoyu
  • Boakye, Kofi

Abrégé

Described are systems and methods for providing a sequential trained machine learning model that may be configured to generate a user embedding that is representative of the user and is configured to predict a plurality of the user's actions over a period of time. The exemplary sequential trained machine learning model may be employed, for example, in connection with recommendation, search, and/or other services. Exemplary embodiments of the present disclosure may also employ the user embeddings generated by the exemplary sequential trained machine learning model in connection with one or more conditional retrieval systems that may include an end-to-end learned model, which are configured to generate updated user embeddings based on the user embeddings generated by the exemplary sequential trained machine learning model and certain contextual information.

Classes IPC  ?

  • G06N 3/045 - Combinaisons de réseaux
  • G06F 16/9535 - Adaptation de la recherche basée sur les profils des utilisateurs et la personnalisation
  • G06N 3/08 - Méthodes d'apprentissage

53.

MULTI-MODAL PRODUCT EMBEDDING GENERATOR

      
Numéro d'application 18167002
Statut En instance
Date de dépôt 2023-02-09
Date de la première publication 2023-08-10
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Baltescu, Paul
  • Zhai, Andrew Huan
  • Chen, Haoyu
  • Leskovec, Jurij
  • Pancha, Nikil
  • Rosenberg, Charles Joseph

Abrégé

Described are systems and methods for providing a multi-tasked trained machine learning model that may be configured to generate product embeddings from multiple types of product information. The exemplary product embeddings may be generated for a corpus of products (e.g., products included in a product catalog, etc.) based on both image information and text information associated with each respective product. Accordingly, the generated product embeddings may be compatible with learned representations of the different types of product information (e.g., image information, text information, etc.) and may be used to create a product index, which can be used to determine and serve product recommendations in connection with multiple different recommendation services that may be configured to receive different types of inputs (e.g., a single image, multiple images, text-based information, etc.).

Classes IPC  ?

  • G06Q 30/0601 - Commerce électronique [e-commerce]
  • G06F 16/9038 - Présentation des résultats des requêtes
  • G06F 16/901 - IndexationStructures de données à cet effetStructures de stockage

54.

Textual and image based search

      
Numéro d'application 18295182
Numéro de brevet 12174884
Statut Délivré - en vigueur
Date de dépôt 2023-04-03
Date de la première publication 2023-08-10
Date d'octroi 2024-12-24
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Kislyuk, Dmitry Olegovich
  • Harris, Jeffrey
  • Herasymenko, Anton
  • Kim, Eric
  • Jen, Yiming

Abrégé

Described is a system and method for enabling visual search for information. With each selection of an object included in an image, additional images that include visually similar objects are determined and presented to the user.

Classes IPC  ?

  • G06F 16/00 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet
  • G06F 16/2457 - Traitement des requêtes avec adaptation aux besoins de l’utilisateur
  • G06F 16/248 - Présentation des résultats de requêtes
  • G06F 16/56 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet de données d’images fixes en format vectoriel
  • G06F 16/58 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
  • G06F 16/583 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des métadonnées provenant automatiquement du contenu
  • G06F 16/738 - Présentation des résultats des requêtes

55.

Image keywords

      
Numéro d'application 17315197
Numéro de brevet 11720626
Statut Délivré - en vigueur
Date de dépôt 2021-05-07
Date de la première publication 2023-08-08
Date d'octroi 2023-08-08
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Koy, Albert
  • Wang, Xiaodong

Abrégé

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing content. One of the methods includes receiving a target image at an image platform; determining one or more images related to the target image; determining queries associated with the related images; deriving candidate keywords from the determined queries; filtering the candidate keywords to select one or more keywords; and providing the image to one or more users in response to respective incoming queries based on the one or more keywords.

Classes IPC  ?

  • G06F 16/00 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet
  • G06F 16/58 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
  • G06F 16/583 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des métadonnées provenant automatiquement du contenu
  • G06F 16/248 - Présentation des résultats de requêtes

56.

DYNAMIC SEARCH INPUT SELECTION

      
Numéro d'application 18186017
Statut En instance
Date de dépôt 2023-03-17
Date de la première publication 2023-07-20
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Xu, Kelei
  • Gavini, Naveen
  • Jing, Yushi
  • Zhai, Andrew Huan
  • Kislyuk, Dmitry Olegovich

Abrégé

Described is a system and method for enabling dynamic selection of a search input. For example, rather than having a static search input box, the search input may be dynamically positioned such that it encompasses a portion of displayed information. An image segment that includes a representation of the encompassed portion of the displayed information is generated and processed to determine an object represented in the portion of the displayed information. Additional images with visually similar representations of objects are then determined and presented to the user.

Classes IPC  ?

  • G06F 16/58 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
  • G06F 16/54 - NavigationVisualisation à cet effet
  • G06F 16/532 - Formulation de requêtes, p. ex. de requêtes graphiques
  • G06F 16/538 - Présentation des résultats des requêtes
  • G06F 18/22 - Critères d'appariement, p. ex. mesures de proximité
  • G06F 3/04812 - Techniques d’interaction fondées sur l’aspect ou le comportement du curseur, p. ex. sous l’influence de la présence des objets affichés
  • G06F 3/04842 - Sélection des objets affichés ou des éléments de texte affichés
  • G06F 3/04886 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] utilisant des caractéristiques spécifiques fournies par le périphérique d’entrée, p. ex. des fonctions commandées par la rotation d’une souris à deux capteurs, ou par la nature du périphérique d’entrée, p. ex. des gestes en fonction de la pression exercée enregistrée par une tablette numérique utilisant un écran tactile ou une tablette numérique, p. ex. entrée de commandes par des tracés gestuels par partition en zones à commande indépendante de la surface d’affichage de l’écran tactile ou de la tablette numérique, p. ex. claviers virtuels ou menus

57.

Extracted image segments collage

      
Numéro d'application 17666997
Numéro de brevet 12322009
Statut Délivré - en vigueur
Date de dépôt 2022-02-08
Date de la première publication 2023-06-22
Date d'octroi 2025-06-03
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Temple, David
  • Probasco, Ryan Wilson
  • Farre, Albert Pereta
  • Ramkumar, Steven
  • Mahadev, Rohan
  • Zhao, Luke
  • Kislyuk, Dmitry Olegovich
  • Xue, David Ding-Jia

Abrégé

Described are systems and methods to extract image segments from an image and include those extracted image segments in a collage. The origin information, such as the source image, source image location, etc., from which the extracted image segment is generated is maintained as metadata so that interaction with the extracted image segment on the collage can be used to determine and/or return to the origin of the extracted image segment. Collages may be updated, shared, adjusted, etc., by the creator of the collage or other users.

Classes IPC  ?

  • G06F 17/00 - Équipement ou méthodes de traitement de données ou de calcul numérique, spécialement adaptés à des fonctions spécifiques
  • G06Q 30/0601 - Commerce électronique [e-commerce]
  • G06T 7/11 - Découpage basé sur les zones
  • G06T 11/60 - Édition de figures et de texteCombinaison de figures ou de texte
  • G06V 10/25 - Détermination d’une région d’intérêt [ROI] ou d’un volume d’intérêt [VOI]
  • G06V 10/26 - Segmentation de formes dans le champ d’imageDécoupage ou fusion d’éléments d’image visant à établir la région de motif, p. ex. techniques de regroupementDétection d’occlusion
  • G06V 10/774 - Génération d'ensembles de motifs de formationTraitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source méthodes de Bootstrap, p. ex. "bagging” ou “boosting”
  • G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux

58.

EXTRACTED IMAGE SEGMENTS COLLAGE

      
Numéro d'application US2022081875
Numéro de publication 2023/115044
Statut Délivré - en vigueur
Date de dépôt 2022-12-16
Date de publication 2023-06-22
Propriétaire PINTEREST, INC. (USA)
Inventeur(s)
  • Temple, David
  • Probasco, Ryan, Wilson
  • Farre, Albert, Pereta
  • Ramkumar, Steven
  • Mahadev, Rohan
  • Zhao, Luke
  • Kislyuk, Dmitry, Olegovich
  • Xue, David, Ding-Jia

Abrégé

Described are systems and methods to extract image segments from an image and include those extracted image segments in a collage. The origin information, such as the source image, source image location, etc., from which the extracted image segment is generated is maintained as metadata so that interaction with the extracted image segment on the collage can be used to determine and/or return to the origin of the extracted image segment. Collages may be updated, shared, adjusted, etc., by the creator of the collage or other users.

Classes IPC  ?

59.

Identifying content items in response to a text-based request

      
Numéro d'application 18148386
Numéro de brevet 11841897
Statut Délivré - en vigueur
Date de dépôt 2022-12-29
Date de la première publication 2023-06-15
Date d'octroi 2023-12-12
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Pancha, Nikil
  • Zhai, Andrew Huan
  • Rosenberg, Charles Joseph

Abrégé

Systems and methods for responding to a subscriber's text-based request for content items are presented. In response to a request from a subscriber, word pieces are generated from the text-based terms of the request. A request embedding vector of the word pieces is obtained from a trained machine learning model. Using the request embedding vector, a set of content items, from a corpus of content items, is identified. At least some content items of the set of content items are returned to the subscriber in response to the text-based request for content items.

Classes IPC  ?

  • G06F 16/00 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet
  • G06F 16/483 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des métadonnées provenant automatiquement du contenu
  • G06N 20/00 - Apprentissage automatique
  • G06F 16/44 - NavigationVisualisation à cet effet
  • G06F 16/45 - GroupementClassement
  • G06F 40/56 - Génération de langage naturel

60.

Identifying similar content in a multi-item embedding space

      
Numéro d'application 18163716
Numéro de brevet 12475171
Statut Délivré - en vigueur
Date de dépôt 2023-02-02
Date de la première publication 2023-06-08
Date d'octroi 2025-11-18
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Zhai, Andrew Huan
  • Chen, Kaifeng
  • Rosenberg, Charles Joseph

Abrégé

Systems and methods for identifying content for an input query are presented. A mapping model is trained to map elements of an input query embedding vector for a received query into one or more elements of a destination embedding vector. In response to receiving an input query, an input query embedding vector is generated that projects into an input query embedding space. The input query embedding vector is processed by the mapping model to map the input query embedding vector into one or more elements of a destination embedding vector in a destination embedding space, resulting in a partial destination embedding vector. Items of a corpus of content are projected into the destination embedding space and the partial destination embedding vector is also projected into the destination embedding space. A similarity measure determines the most-similar items to the partial destination embedding vector and at least some of the most-similar items are returned in response to the input query.

Classes IPC  ?

  • G06F 16/9038 - Présentation des résultats des requêtes
  • G06F 16/84 - Mise en correspondanceConversion
  • G06F 16/9032 - Formulation de requêtes
  • G06F 16/958 - Organisation ou gestion de contenu de sites Web, p. ex. publication, conservation de pages ou liens automatiques

61.

S

      
Numéro d'application 1730063
Statut Enregistrée
Date de dépôt 2022-12-22
Date d'enregistrement 2022-12-22
Propriétaire Pinterest, Inc. (USA)
Classes de Nice  ?
  • 09 - Appareils et instruments scientifiques et électriques
  • 35 - Publicité; Affaires commerciales
  • 38 - Services de télécommunications
  • 42 - Services scientifiques, technologiques et industriels, recherche et conception
  • 45 - Services juridiques; services de sécurité; services personnels pour individus

Produits et services

Computer software, namely, software that allows users to interact online with information and media content that other users share, and software that allows users to discover, access and share information about, and media content concerning, goods, services, and experiences; computer software and software applications that enable electronic communications network users to create, upload, bookmark, view, annotate, and share data, information and media content; software, downloadable or prerecorded, in the nature of a mobile application that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; software downloadable via electronic communications networks and wireless devices that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; software to facilitate business promotion, connecting social network users with businesses; downloadable electronic publications in the nature of blogs, photographs, and graphic art in the field of general human interest; computer e-commerce software to allow users to perform electronic business transactions via a global computer network; software applications that enable electronic communications network users to create, upload, bookmark, view, annotate, and share data, information and media content; software, downloadable or prerecorded, in the nature of a mobile application that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; software downloadable via electronic communications networks and wireless devices that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content. Advertising and promotional services; advertising and marketing services, namely, promoting the products and services of others; business data analysis; business monitoring and consulting services, namely, data and behavior analysis to provide strategy, insight, and marketing guidance, and for analyzing, understanding and predicting behavior and motivations, and market trends; promoting the goods and services of others by means of operating an online platform with hyperlinks to the resources of others; providing consumer product information relating to consumer, business, and industrial goods of others via an online searchable database; electronic commerce services, namely, providing information about products via telecommunication networks for advertising and sales purposes. Electronic bulletin board services. Providing a platform featuring technology that enables internet users to create, upload, bookmark, view, annotate, share and discover data, information and multimedia content; computer services, namely, creating an online community for registered users to participate in discussions, get feedback from their peers, form virtual communities, and engage in social networking services in the field of general interest; providing online non-downloadable software that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content via a website; providing a platform featuring non-downloadable software that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; hosting an interactive platform and online non-downloadable software for uploading, posting, showing, displaying, tagging, sharing and transmitting messages, comments, multimedia content, photos, pictures, images, text, information, and other user-generated content; developing and hosting a server on a global computer network for the purpose of facilitating e-commerce via such a server; platform and facility for mobile device communication, namely, providing non-downloadable software that facilitates sharing and discovering information and media content via mobile devices; platform and facility for networked communications, namely, providing non-downloadable software that facilitates sharing and discovering information and media content via local and global computer, mobile, cellular, electronic, wireless, and data communications networks. Providing online social networking services for purposes of commentary, comparison, collaboration, consultation, evaluation, advice, discussion, research, notification, reporting, identification, information sharing, indexing, information location, entertainment, pleasure, or general interest.

62.

Virtual Browser For Retail Crawling Engine

      
Numéro d'application 17486556
Statut En instance
Date de dépôt 2021-09-27
Date de la première publication 2023-03-30
Propriétaire PINTEREST, INC. (USA)
Inventeur(s)
  • Aggarwal, Amit
  • Zaytsev, Andrey
  • Gilfanov, Ruslan

Abrégé

A computer system extracts product data from a website and correlates product records from multiple sources to one another as corresponding to the same product. A website is crawled efficiently by rendering webpages using a virtual browser that ignores blacklisted elements, extracts data from objects without rendering, and suppressing retrieval of remote resources. Data is extracted according to engine control statements including a selector and extractor. A website may be crawled repeatedly and changes in extracted data may be detected and flagged. Engine control statements may be automatically changed in response to detecting a change in the configuration of the website. Images of product records may be correlated with one another by first comparing text of the product records and selecting images for comparison based on composition. Images are compared using a machine learning model. Images determined to be similar may be presented to a human for a correlation decision.

Classes IPC  ?

  • G06Q 30/06 - Transactions d’achat, de vente ou de crédit-bail
  • G06Q 30/02 - MarketingEstimation ou détermination des prixCollecte de fonds
  • G06F 16/951 - IndexationTechniques d’exploration du Web
  • G06F 16/958 - Organisation ou gestion de contenu de sites Web, p. ex. publication, conservation de pages ou liens automatiques

63.

Data extraction approach for retail crawling engine

      
Numéro d'application 17486562
Numéro de brevet 12423361
Statut Délivré - en vigueur
Date de dépôt 2021-09-27
Date de la première publication 2023-03-30
Date d'octroi 2025-09-23
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Aggarwal, Amit
  • Zaytsev, Andrey
  • Gilfanov, Ruslan

Abrégé

A computer system extracts product data from a website and correlates product records from multiple sources to one another as corresponding to the same product. A website is crawled efficiently by rendering webpages using a virtual browser that ignores blacklisted elements, extracts data from objects without rendering, and suppressing retrieval of remote resources. Data is extracted according to engine control statements including a selector and extractor. A website may be crawled repeatedly and changes in extracted data may be detected and flagged. Engine control statements may be automatically changed in response to detecting a change in the configuration of the website. Images of product records may be correlated with one another by first comparing text of the product records and selecting images for comparison based on composition. Images are compared using a machine learning model. Images determined to be similar may be presented to a human for a correlation decision.

Classes IPC  ?

  • G06F 16/951 - IndexationTechniques d’exploration du Web
  • G06F 16/958 - Organisation ou gestion de contenu de sites Web, p. ex. publication, conservation de pages ou liens automatiques
  • G06Q 30/0201 - Modélisation du marchéAnalyse du marchéCollecte de données du marché

64.

Efficient deserialization from standardized data files

      
Numéro d'application 17141911
Numéro de brevet 11615109
Statut Délivré - en vigueur
Date de dépôt 2021-01-05
Date de la première publication 2023-03-28
Date d'octroi 2023-03-28
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Pandit, Bhalchandra
  • Xie, Siyang

Abrégé

Systems and methods for de-serializing one or more data elements of a serialized structured data record are presented. In response to a request to de-serialize one or more data elements of a serialized structured data record of a first type, the location of the serialized structured data record is determined within a data file containing a plurality of serialized structured data records. Locations of the data of the one or more data elements are determined and the data of the one or more data elements is retrieved. The data is de-serialized and stored in corresponding data elements in an instantiated structured data record of the first type. The one or more data elements that are de-serialized are fewer than all of the data elements of the serialized structured data record.

Classes IPC  ?

  • G06F 16/25 - Systèmes d’intégration ou d’interfaçage impliquant les systèmes de gestion de bases de données
  • G06F 16/178 - Techniques de synchronisation des fichiers dans les systèmes de fichiers

65.

FACILITATING PURCHASE OF OBJECTS

      
Numéro d'application 18053188
Statut En instance
Date de dépôt 2022-11-07
Date de la première publication 2023-03-23
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Jenkins, Jon
  • Lee, Catherine Cissy

Abrégé

This disclosure describes systems and methods that facilitate purchase of objects from merchants. For example, a user may browse a website available from an object management service and identify objects that they desire to purchase. Rather than having to locate the seller of those objects to make a purchase, the implementations described herein facilitate a connection between the user and the merchant so that the merchant's sales are increased and the user is provided an efficient and safe shopping experience.

Classes IPC  ?

  • G06Q 30/06 - Transactions d’achat, de vente ou de crédit-bail

66.

SHUFFLES

      
Numéro d'application 1714918
Statut Enregistrée
Date de dépôt 2022-12-22
Date d'enregistrement 2022-12-22
Propriétaire Pinterest, Inc. (USA)
Classes de Nice  ?
  • 09 - Appareils et instruments scientifiques et électriques
  • 35 - Publicité; Affaires commerciales
  • 38 - Services de télécommunications
  • 42 - Services scientifiques, technologiques et industriels, recherche et conception
  • 45 - Services juridiques; services de sécurité; services personnels pour individus

Produits et services

Computer software, namely, software that allows users to interact online with information and media content that other users share, and software that allows users to discover, access and share information about, and media content concerning, goods, services, and experiences; computer software and software applications that enable electronic communications network users to create, upload, bookmark, view, annotate, and share data, information and media content; software, downloadable or prerecorded, in the nature of a mobile application that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; software downloadable via electronic communications networks and wireless devices that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; software to facilitate business promotion, connecting social network users with businesses; downloadable electronic publications in the nature of blogs, photographs, and graphic art in the field of general human interest; computer e-commerce software to allow users to perform electronic business transactions via a global computer network; software applications that enable electronic communications network users to create, upload, bookmark, view, annotate, and share data, information and media content; software, downloadable or prerecorded, in the nature of a mobile application that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; software downloadable via electronic communications networks and wireless devices that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content. Advertising and promotional services; advertising and marketing services, namely, promoting the products and services of others; business data analysis; business monitoring and consulting services, namely, data and behavior analysis to provide strategy, insight, and marketing guidance, and for analyzing, understanding and predicting behavior and motivations, and market trends; promoting the goods and services of others by means of operating an online platform with hyperlinks to the resources of others; providing consumer product information relating to consumer, business, and industrial goods of others via an online searchable database; electronic commerce services, namely, providing information about products via telecommunication networks for advertising and sales purposes. Electronic bulletin board services. Providing a platform featuring technology that enables internet users to create, upload, bookmark, view, annotate, share and discover data, information and multimedia content; computer services, namely, creating an online community for registered users to participate in discussions, get feedback from their peers, form virtual communities, and engage in social networking services in the field of general interest; providing online non-downloadable software that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content via a website; providing a platform featuring non-downloadable software that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; hosting an interactive platform and online non-downloadable software for uploading, posting, showing, displaying, tagging, sharing and transmitting messages, comments, multimedia content, photos, pictures, images, text, information, and other user-generated content; developing and hosting a server on a global computer network for the purpose of facilitating e-commerce via such a server; platform and facility for mobile device communication, namely, providing non-downloadable software that facilitates sharing and discovering information and media content via mobile devices; platform and facility for networked communications, namely, providing non-downloadable software that facilitates sharing and discovering information and media content via local and global computer, mobile, cellular, electronic, wireless, and data communications networks. Providing online social networking services for purposes of commentary, comparison, collaboration, consultation, evaluation, advice, discussion, research, notification, reporting, identification, information sharing, indexing, information location, entertainment, pleasure, or general interest.

67.

S SHUFFLES

      
Numéro d'application 1715592
Statut Enregistrée
Date de dépôt 2022-12-22
Date d'enregistrement 2022-12-22
Propriétaire Pinterest, Inc. (USA)
Classes de Nice  ?
  • 09 - Appareils et instruments scientifiques et électriques
  • 35 - Publicité; Affaires commerciales
  • 38 - Services de télécommunications
  • 42 - Services scientifiques, technologiques et industriels, recherche et conception
  • 45 - Services juridiques; services de sécurité; services personnels pour individus

Produits et services

Computer software, namely, software that allows users to interact online with information and media content that other users share, and software that allows users to discover, access and share information about, and media content concerning, goods, services, and experiences; computer software and software applications that enable electronic communications network users to create, upload, bookmark, view, annotate, and share data, information and media content; software, downloadable or prerecorded, in the nature of a mobile application that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; software downloadable via electronic communications networks and wireless devices that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; software to facilitate business promotion, connecting social network users with businesses; downloadable electronic publications in the nature of blogs, photographs, and graphic art in the field of general human interest; computer e-commerce software to allow users to perform electronic business transactions via a global computer network. Advertising and promotional services; advertising and marketing services, namely, promoting the products and services of others; business data analysis; business monitoring and consulting services, namely, data and behavior analysis to provide strategy, insight, and marketing guidance, and for analyzing, understanding and predicting behavior and motivations, and market trends; promoting the goods and services of others by means of operating an online platform with hyperlinks to the resources of others; providing consumer product information relating to consumer, business, and industrial goods of others via an online searchable database; electronic commerce services, namely, providing information about products via telecommunication networks for advertising and sales purposes. Electronic bulletin board services. Providing a platform featuring technology that enables internet users to create, upload, bookmark, view, annotate, share and discover data, information and multimedia content; computer services, namely, creating an online community for registered users to participate in discussions, get feedback from their peers, form virtual communities, and engage in social networking services in the field of general interest; providing online non-downloadable software that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content via a website; providing a platform featuring non-downloadable software that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; hosting an interactive platform and online non-downloadable software for uploading, posting, showing, displaying, tagging, sharing and transmitting messages, comments, multimedia content, photos, pictures, images, text, information, and other user-generated content; developing and hosting a server on a global computer network for the purpose of facilitating e-commerce via such a server; platform and facility for mobile device communication, namely, providing non-downloadable software that facilitates sharing and discovering information and media content via mobile devices; platform and facility for networked communications, namely, providing non-downloadable software that facilitates sharing and discovering information and media content via local and global computer, mobile, cellular, electronic, wireless, and data communications networks. Providing online social networking services for purposes of commentary, comparison, collaboration, consultation, evaluation, advice, discussion, research, notification, reporting, identification, information sharing, indexing, information location, entertainment, pleasure, or general interest.

68.

Non-fungible token authentication

      
Numéro d'application 17394352
Numéro de brevet 11985253
Statut Délivré - en vigueur
Date de dépôt 2021-08-04
Date de la première publication 2023-02-09
Date d'octroi 2024-05-14
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Milam, Evrhet
  • Black, Tiffany C.
  • Probasco, Ryan Wilson
  • Fu, Will
  • Temple, David
  • Kislyuk, Dmitry Olegovich
  • Gusev, Andrey Dmitriyevich

Abrégé

Disclosed are systems and methods that authenticate non-fungible tokens (“NFT”) and/or digital data represented by or pointed to by an NFT. In some implementations, authentication may be with respect to an existing NFT. In other implementations, authentication may be with respect to an NFT that is being created. The disclosed implementations may compare a candidate and/or candidate NFT data with existing NFTs and/or existing NFT data to determine if the candidate NFT and/or candidate NFT data is similar to other NFTs and/or other NFT data of another NFT, which may exist on any of many different blockchains.

Classes IPC  ?

  • H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
  • G06F 18/214 - Génération de motifs d'entraînementProcédés de Bootstrapping, p. ex. ”bagging” ou ”boosting”
  • G06N 20/00 - Apprentissage automatique
  • H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
  • H04L 9/06 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité l'appareil de chiffrement utilisant des registres à décalage ou des mémoires pour le codage par blocs, p. ex. système DES
  • H04L 9/08 - Répartition de clés
  • H04L 9/30 - Clé publique, c.-à-d. l'algorithme de chiffrement étant impossible à inverser par ordinateur et les clés de chiffrement des utilisateurs n'exigeant pas le secret

69.

NON-FUNGIBLE TOKEN AUTHENTICATION

      
Numéro d'application US2022038852
Numéro de publication 2023/014604
Statut Délivré - en vigueur
Date de dépôt 2022-07-29
Date de publication 2023-02-09
Propriétaire PINTEREST, INC. (USA)
Inventeur(s)
  • Milam, Evrhet
  • Black, Tiffany C.
  • Probasco, Ryan Wilson
  • Fu, Will
  • Temple, David
  • Kislyuk, Dmitry Olegovich
  • Gusev, Andrey Dmitriyevich

Abrégé

Disclosed are systems and methods that authenticate non-fungible tokens ("NFT") and/or digital data represented by or pointed to by an NFT. In some implementations, authentication may be with respect to an existing NFT. In other implementations, authentication may be with respect to an NFT that is being created. The disclosed implementations may compare a candidate and/or candidate NFT data with existing NFTs and/or existing NFT data to determine if the candidate NFT and/or candidate NFT data is similar to other NFTs and/or other NFT data of another NFT, which may exist on any of many different blockchains.

Classes IPC  ?

  • H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
  • H04L 9/40 - Protocoles réseaux de sécurité
  • G06F 16/2457 - Traitement des requêtes avec adaptation aux besoins de l’utilisateur

70.

Identifying similar content in a multi-item embedding space

      
Numéro d'application 16712140
Numéro de brevet 11574020
Statut Délivré - en vigueur
Date de dépôt 2019-12-12
Date de la première publication 2023-02-07
Date d'octroi 2023-02-07
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Zhai, Andrew Huan
  • Chen, Kaifeng
  • Rosenberg, Charles Joseph

Abrégé

Systems and methods for identifying content for an input query are presented. A mapping model is trained to map elements of an input query embedding vector for a received query into one or more elements of a destination embedding vector. In response to receiving an input query, an input query embedding vector is generated that projects into an input query embedding space. The input query embedding vector is processed by the mapping model to map the input query embedding vector into one or more elements of a destination embedding vector in a destination embedding space, resulting in a partial destination embedding vector. Items of a corpus of content are projected into the destination embedding space and the partial destination embedding vector is also projected into the destination embedding space. A similarity measure determines the most-similar items to the partial destination embedding vector and at least some of the most-similar items are returned in response to the input query.

Classes IPC  ?

  • G06F 16/9038 - Présentation des résultats des requêtes
  • G06F 16/958 - Organisation ou gestion de contenu de sites Web, p. ex. publication, conservation de pages ou liens automatiques
  • G06F 16/9032 - Formulation de requêtes
  • G06F 16/84 - Mise en correspondanceConversion

71.

Generating personalized content

      
Numéro d'application 15835158
Numéro de brevet 11574371
Statut Délivré - en vigueur
Date de dépôt 2017-12-07
Date de la première publication 2023-02-07
Date d'octroi 2023-02-07
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Hosseini, Farid
  • Shah, Salil

Abrégé

Systems and methods are presented for adding system-identified content to a user's content space based on information identified from the user's email account. In operation, after obtaining user authorization to access email items of an email account, the email items are iteratively processed. In processing each of the email items, one or more topics of a currently processed email item are identified. Based on the identified topics and user preferences, one or more content items may be identified for addition to the user's online content space. Additionally, the information identified from processing the one or more email items is used to update the user's preferences.

Classes IPC  ?

  • G06Q 30/00 - Commerce
  • G06Q 50/00 - Technologies de l’information et de la communication [TIC] spécialement adaptées à la mise en œuvre des procédés d’affaires d’un secteur particulier d’activité économique, p. ex. aux services d’utilité publique ou au tourisme
  • G06Q 30/02 - MarketingEstimation ou détermination des prixCollecte de fonds

72.

MATCHING USER PROVIDED REPRESENTATIONS OF ITEMS WITH SELLERS OF THOSE ITEMS

      
Numéro d'application 17930631
Statut En instance
Date de dépôt 2022-09-08
Date de la première publication 2023-01-05
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Yamartino, Michael
  • Wang, Chao
  • Thatipamala, Sridatta Kaustubh
  • Wei, Yuan

Abrégé

This disclosure describes systems and methods for matching user provided images that include representations of items with sellers of those items. A management service, as described herein, may provide a web site where users can post images, view images, share images, correspond with other users, etc. The management service may identify items represented in the images and determine one or more sellers that offer those items for sale. When another user requests to view the user provided image, the image, seller information identifying the seller determined to sell the item represented in the image, and/or a purchase control that may be selected by a user to initiate a purchase with the seller is presented.

Classes IPC  ?

  • G06Q 30/06 - Transactions d’achat, de vente ou de crédit-bail
  • G06Q 30/02 - MarketingEstimation ou détermination des prixCollecte de fonds

73.

Identifying content items in response to a text-based request

      
Numéro d'application 16998398
Numéro de brevet 11544317
Statut Délivré - en vigueur
Date de dépôt 2020-08-20
Date de la première publication 2023-01-03
Date d'octroi 2023-01-03
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Pancha, Nikil
  • Zhai, Andrew Huan
  • Rosenberg, Charles Joseph

Abrégé

Systems and methods for responding to a subscriber's text-based request for content items are presented. In response to a request from a subscriber, word pieces are generated from the text-based terms of the request. A request embedding vector of the word pieces is obtained from a trained machine learning model. Using the request embedding vector, a set of content items, from a corpus of content items, is identified. At least some content items of the set of content items are returned to the subscriber in response to the text-based request for content items.

Classes IPC  ?

  • G06F 16/00 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet
  • G06F 16/483 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des métadonnées provenant automatiquement du contenu
  • G06N 20/00 - Apprentissage automatique
  • G06F 16/44 - NavigationVisualisation à cet effet
  • G06F 16/45 - GroupementClassement
  • G06F 40/56 - Génération de langage naturel

74.

Predictively identifying activity subscribers

      
Numéro d'application 16231441
Numéro de brevet 11538048
Statut Délivré - en vigueur
Date de dépôt 2018-12-22
Date de la première publication 2022-12-27
Date d'octroi 2022-12-27
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Nahta, Mohak
  • Lien, Henry

Abrégé

Systems and methods for predictively identifying content sources as likely activity subscribers to an online service is presented. In view of a corpus of activity data describing activity of users of an online service, an analysis of this corpus of activity data is carried out to identify one or more content sources that are not activity subscribers but whose content is posted on the online service. A machine learning model is employed to predictively identify at least some content sources that are not activity subscribers of the online service that could likely become activity subscribers. A first content source of the one or more content sources is identified as a likely potential activity subscriber according to the trained machine learning model and the first content source is notified with information for becoming an activity subscriber.

Classes IPC  ?

  • G06Q 30/02 - MarketingEstimation ou détermination des prixCollecte de fonds
  • G06N 20/00 - Apprentissage automatique

75.

SHUFFLES

      
Numéro d'application 224138700
Statut En instance
Date de dépôt 2022-12-22
Propriétaire Pinterest, Inc. (USA)
Classes de Nice  ?
  • 09 - Appareils et instruments scientifiques et électriques
  • 35 - Publicité; Affaires commerciales
  • 38 - Services de télécommunications
  • 42 - Services scientifiques, technologiques et industriels, recherche et conception
  • 45 - Services juridiques; services de sécurité; services personnels pour individus

Produits et services

(1) Computer software, namely, software that allows users to interact online with information and media content that other users share, and software that allows users to discover, access and share information about, and media content concerning, goods, services, and experiences; computer software and software applications that enable electronic communications network users to create, upload, bookmark, view, annotate, and share data, information and media content; software, downloadable or prerecorded, in the nature of a mobile application that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; software downloadable via electronic communications networks and wireless devices that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; software to facilitate business promotion, connecting social network users with businesses; downloadable electronic publications in the nature of blogs, photographs, and graphic art in the field of general human interest; computer e-commerce software to allow users to perform electronic business transactions via a global computer network (2) Software applications that enable electronic communications network users to create, upload, bookmark, view, annotate, and share data, information and media content; software, downloadable or prerecorded, in the nature of a mobile application that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; software downloadable via electronic communications networks and wireless devices that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content (1) Providing consumer product information relating to consumer, business, and industrial goods of others via an online searchable database (2) Providing online non-downloadable software that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content via a website (3) Advertising and promotional services; advertising and marketing services, namely, promoting the products and services of others; business data analysis; business monitoring and consulting services, namely, data and behavior analysis to provide strategy, insight, and marketing guidance, and for analyzing, understanding and predicting behavior and motivations, and market trends; promoting the goods and services of others by means of operating an online platform with hyperlinks to the resources of others; providing an online searchable database featuring a wide variety of consumer, business, and industrial goods of others; electronic commerce services, namely, providing information about products via telecommunication networks for advertising and sales purposes (4) Electronic bulletin board services (5) Providing a platform featuring technology that enables internet users to create, upload, bookmark, view, annotate, share and discover data, information and multimedia content; computer services, namely, creating an online community for registered users to participate in discussions, get feedback from their peers, form virtual communities, and engage in social networking services in the field of general interest; providing a website featuring non-downloadable software that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; providing a platform featuring non-downloadable software that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; hosting an interactive platform and online non-downloadable software for uploading, posting, showing, displaying, tagging, sharing and transmitting messages, comments, multimedia content, photos, pictures, images, text, information, and other user-generated content; developing and hosting a server on a global computer network for the purpose of facilitating e-commerce via such a server; platform and facility for mobile device communication, namely, providing non-downloadable software that facilitates sharing and discovering information and media content via mobile devices; platform and facility for networked communications, namely, providing non-downloadable software that facilitates sharing and discovering information and media content via local and global computer, mobile, cellular, electronic, wireless, and data communications networks (6) Providing online social networking services for purposes of commentary, comparison, collaboration, consultation, evaluation, advice, discussion, research, notification, reporting, identification, information sharing, indexing, information location, entertainment, pleasure, or general interest

76.

S

      
Numéro d'application 225850300
Statut En instance
Date de dépôt 2022-12-22
Propriétaire Pinterest, Inc. (USA)
Classes de Nice  ?
  • 09 - Appareils et instruments scientifiques et électriques
  • 35 - Publicité; Affaires commerciales
  • 38 - Services de télécommunications
  • 42 - Services scientifiques, technologiques et industriels, recherche et conception
  • 45 - Services juridiques; services de sécurité; services personnels pour individus

Produits et services

(1) Computer software, namely, software that allows users to interact online with information and media content that other users share, and software that allows users to discover, access and share information about, and media content concerning, goods, services, and experiences; computer software and software applications that enable electronic communications network users to create, upload, bookmark, view, annotate, and share data, information and media content; software, downloadable or prerecorded, in the nature of a mobile application that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; software downloadable via electronic communications networks and wireless devices that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; software to facilitate business promotion, connecting social network users with businesses; downloadable electronic publications in the nature of blogs, photographs, and graphic art in the field of general human interest; computer e-commerce software to allow users to perform electronic business transactions via a global computer network; software applications that enable electronic communications network users to create, upload, bookmark, view, annotate, and share data, information and media content; software, downloadable or prerecorded, in the nature of a mobile application that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; software downloadable via electronic communications networks and wireless devices that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content. (1) Advertising and promotional services; advertising and marketing services, namely, promoting the products and services of others; business data analysis; business monitoring and consulting services, namely, data and behavior analysis to provide strategy, insight, and marketing guidance, and for analyzing, understanding and predicting behavior and motivations, and market trends; promoting the goods and services of others by means of operating an online platform with hyperlinks to the resources of others; providing consumer product information relating to consumer, business, and industrial goods of others via an online searchable database; electronic commerce services, namely, providing information about products via telecommunication networks for advertising and sales purposes. (2) Providing a platform featuring technology that enables internet users to create, upload, bookmark, view, annotate, share and discover data, information and multimedia content; computer services, namely, creating an online community for registered users to participate in discussions, get feedback from their peers, form virtual communities, and engage in social networking services in the field of general interest; providing online non-downloadable software that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content via a website; providing a platform featuring non-downloadable software that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; hosting an interactive platform and online non-downloadable software for uploading, posting, showing, displaying, tagging, sharing and transmitting messages, comments, multimedia content, photos, pictures, images, text, information, and other user-generated content; developing and hosting a server on a global computer network for the purpose of facilitating e-commerce via such a server; platform and facility for mobile device communication, namely, providing non-downloadable software that facilitates sharing and discovering information and media content via mobile devices; platform and facility for networked communications, namely, providing non-downloadable software that facilitates sharing and discovering information and media content via local and global computer, mobile, cellular, electronic, wireless, and data communications networks. (3) Electronic bulletin board services (4) Providing online social networking services for purposes of commentary, comparison, collaboration, consultation, evaluation, advice, discussion, research, notification, reporting, identification, information sharing, indexing, information location, entertainment, pleasure, or general interest

77.

S SHUFFLES

      
Numéro d'application 224138600
Statut En instance
Date de dépôt 2022-12-22
Propriétaire Pinterest, Inc. (USA)
Classes de Nice  ?
  • 09 - Appareils et instruments scientifiques et électriques
  • 35 - Publicité; Affaires commerciales
  • 38 - Services de télécommunications
  • 42 - Services scientifiques, technologiques et industriels, recherche et conception
  • 45 - Services juridiques; services de sécurité; services personnels pour individus

Produits et services

(1) Computer software, namely, software that allows users to interact online with information and media content that other users share, and software that allows users to discover, access and share information about, and media content concerning, goods, services, and experiences; computer software and software applications that enable electronic communications network users to create, upload, bookmark, view, annotate, and share data, information and media content; software, downloadable or prerecorded, in the nature of a mobile application that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; software downloadable via electronic communications networks and wireless devices that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; software to facilitate business promotion, connecting social network users with businesses; downloadable electronic publications in the nature of blogs, photographs, and graphic art in the field of general human interest; computer e-commerce software to allow users to perform electronic business transactions via a global computer network. (1) Advertising and promotional services; advertising and marketing services, namely, promoting the products and services of others; business data analysis; business monitoring and consulting services, namely, data and behavior analysis to provide strategy, insight, and marketing guidance, and for analyzing, understanding and predicting behavior and motivations, and market trends; promoting the goods and services of others by means of operating an online platform with hyperlinks to the resources of others; providing consumer product information relating to consumer, business, and industrial goods of others via an online searchable database; electronic commerce services, namely, providing information about products via telecommunication networks for advertising and sales purposes. (2) Electronic bulletin board services. (3) Providing a platform featuring technology that enables internet users to create, upload, bookmark, view, annotate, share and discover data, information and multimedia content; computer services, namely, creating an online community for registered users to participate in discussions, get feedback from their peers, form virtual communities, and engage in social networking services in the field of general interest; providing online non-downloadable software that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content via a website; providing a platform featuring non-downloadable software that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; hosting an interactive platform and online non-downloadable software for uploading, posting, showing, displaying, tagging, sharing and transmitting messages, comments, multimedia content, photos, pictures, images, text, information, and other user-generated content; developing and hosting a server on a global computer network for the purpose of facilitating e-commerce via such a server; platform and facility for mobile device communication, namely, providing non-downloadable software that facilitates sharing and discovering information and media content via mobile devices; platform and facility for networked communications, namely, providing non-downloadable software that facilitates sharing and discovering information and media content via local and global computer, mobile, cellular, electronic, wireless, and data communications networks. (4) Providing online social networking services for purposes of commentary, comparison, collaboration, consultation, evaluation, advice, discussion, research, notification, reporting, identification, information sharing, indexing, information location, entertainment, pleasure, or general interest.

78.

Recommending content to subscribers

      
Numéro d'application 17882882
Numéro de brevet 12079289
Statut Délivré - en vigueur
Date de dépôt 2022-08-08
Date de la première publication 2022-11-24
Date d'octroi 2024-09-03
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Pal, Aditya
  • Eksombatchai, Chantat
  • Zhou, Yitong
  • Zhao, Bo
  • Rosenberg, Charles Joseph
  • Leskovec, Jurij

Abrégé

Systems and methods for recommending content to an online service subscriber are presented. For each subscriber, content items that were the subject of the subscriber's prior interactions are projected, via associated embedding vectors, into a content item embedding space. The content items, via their projections into the content item embedding space, are clustered to form a plurality of interest clusters for the subscriber. A representative embedding vector is determined for each interest cluster, and a plurality of these embedding vectors are stored as the representative embedding vectors for the subscriber. The online service, in response to a request for recommended content for a subscriber, selects a first representative embedding vector associated with the subscriber and identifies a new content item from a corpus of content items according to a similarity measure between the first representative embedding vector and an embedding vector associated with the new content item.

Classes IPC  ?

  • G06F 16/9535 - Adaptation de la recherche basée sur les profils des utilisateurs et la personnalisation
  • G06F 16/906 - GroupementClassement

79.

Content presentation

      
Numéro d'application 17876827
Numéro de brevet 11790024
Statut Délivré - en vigueur
Date de dépôt 2022-07-29
Date de la première publication 2022-11-17
Date d'octroi 2023-10-17
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Lu, Wendy
  • Velo, Justin
  • Tow, Kelvin
  • You, Mengya
  • Crawford, Nicole
  • He, Harrison

Abrégé

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing content. One of the methods includes providing a plurality of image content items to an application interface of a client device for presentation; receiving a user selection of a particular image content item of the plurality of presented image content items; and responsive to the selection, providing a combination of native content and third party content associated with the selected image content item, wherein the native content includes a close up view of the selected image content item and the third party content includes a third party webpage.

Classes IPC  ?

  • G06F 17/00 - Équipement ou méthodes de traitement de données ou de calcul numérique, spécialement adaptés à des fonctions spécifiques
  • G06F 16/954 - Navigation, p. ex. en utilisant la navigation par catégories
  • G06F 3/0485 - Défilement ou défilement panoramique
  • G06F 3/04845 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs pour la transformation d’images, p. ex. glissement, rotation, agrandissement ou changement de couleur
  • G06F 16/54 - NavigationVisualisation à cet effet
  • G06F 16/957 - Optimisation de la navigation, p. ex. mise en cache ou distillation de contenus

80.

Systems and methods for determining a diversity penalty in connection with selecting advertisement content

      
Numéro d'application 16681243
Numéro de brevet 11494804
Statut Délivré - en vigueur
Date de dépôt 2019-11-12
Date de la première publication 2022-11-08
Date d'octroi 2022-11-08
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Datta, Ashim
  • Jung, Dz-Mou
  • Mclaughlin, Kevin
  • Llaca Ojinaga, Javier
  • Xu, Jiajing

Abrégé

Described are systems and methods for determining a diversity function in connection with potential advertisements in determining one or more advertisements to present to a user. This can facilitate presenting diverse advertisements to users. The diversity function can yield a diversity penalty for each potential advertisement to be able to determine a rank order of the potential advertisements. The diversity function can include a repetition score and a multiplier for each potential advertisement.

Classes IPC  ?

  • G06Q 30/02 - MarketingEstimation ou détermination des prixCollecte de fonds
  • G06F 17/18 - Opérations mathématiques complexes pour l'évaluation de données statistiques

81.

Method, medium, and system for facilitating purchase of objects

      
Numéro d'application 16166974
Numéro de brevet 11494826
Statut Délivré - en vigueur
Date de dépôt 2018-10-22
Date de la première publication 2022-11-08
Date d'octroi 2022-11-08
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Jenkins, Jon
  • Lee, Catherine Cissy

Abrégé

This disclosure describes systems and methods that facilitate purchase of objects from merchants. For example, a user may browse a website available from an object management service and identify objects that they desire to purchase. Rather than having to locate the seller of those objects to make a purchase, the implementations described herein facilitate a connection between the user and the merchant so that the merchant's sales are increased and the user is provided an efficient and safe shopping experience.

Classes IPC  ?

82.

OBJECT IDENTIFIERS FOR REAL WORLD OBJECTS

      
Numéro d'application 17860765
Statut En instance
Date de dépôt 2022-07-08
Date de la première publication 2022-10-27
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Gavini, Naveen
  • Wilson, Jason Luke
  • Sharp, Evan

Abrégé

This application describes a system and process for providing object identifiers relating to real world objects to users based on the location of the user and the anticipated interested of the user in an object within a defined distance of the user. For example, if the user is within a retail store, a portable device associated with the user may detect or receive a beacon transmitted from a location within the retail store and object identifiers representative of objects within the store may be generated and provided to the user. In some implementations, only object identifier representative of items determined to be of likely interest to the user may be provided for presentation to the user.

Classes IPC  ?

  • G06Q 30/06 - Transactions d’achat, de vente ou de crédit-bail
  • H04W 4/02 - Services utilisant des informations de localisation

83.

Attribute extraction

      
Numéro d'application 17400037
Numéro de brevet 11768888
Statut Délivré - en vigueur
Date de dépôt 2021-08-11
Date de la première publication 2022-10-13
Date d'octroi 2023-09-26
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Zhuang, Jinfeng
  • Zhao, Zhengda
  • Mohan, Vijai

Abrégé

Disclosed are systems and methods for autonomously extracting attributes from domains of a vertical. The disclosed implementations train a deep neural network (“DNN”) based on one or more domains of a vertical using labeled embedding vectors generated for nodes of those one or more domains. The trained DNN may then be used to autonomously label nodes of other domains within the same vertical such that attributes corresponding to those labels can be extracted.

Classes IPC  ?

  • G06F 16/00 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet
  • G06F 16/951 - IndexationTechniques d’exploration du Web
  • G06N 3/08 - Méthodes d'apprentissage
  • G06F 18/214 - Génération de motifs d'entraînementProcédés de Bootstrapping, p. ex. ”bagging” ou ”boosting”

84.

Visual object graphs

      
Numéro d'application 17848040
Numéro de brevet 11727049
Statut Délivré - en vigueur
Date de dépôt 2022-06-23
Date de la première publication 2022-10-13
Date d'octroi 2023-08-15
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Kim, Eric
  • Kislyuk, Dmitry Olegovich

Abrégé

Disclosed are implementations that enable the linking or connection of objects and different scenes in which those objects are represented. For example, a corpus of scenes (e.g., digital images) that include a representation of one or more objects may be processed using the disclosed implementations to segment from those scenes the individual objects represented in those scenes. The disclosed implementations may further determine clusters of visually similar object segments and form object clusters for those object segments. The scenes that include those object segments are also linked to the object cluster. With scenes linked to different object clusters, a user may select one or more query objects or a query scene and be presented with other scenes that include visually similar objects, even though the overall scenes may be visually different.

Classes IPC  ?

  • G06F 16/55 - GroupementClassement
  • G06T 7/10 - DécoupageDétection de bords
  • G06F 17/16 - Calcul de matrice ou de vecteur
  • G06V 20/30 - ScènesÉléments spécifiques à la scène dans les albums, les collections ou les contenus partagés, p. ex. des photos ou des vidéos issus des réseaux sociaux
  • G06F 18/22 - Critères d'appariement, p. ex. mesures de proximité
  • G06F 18/23 - Techniques de partitionnement
  • G06F 16/51 - IndexationStructures de données à cet effetStructures de stockage

85.

Generating neighborhood convolutions within a large network

      
Numéro d'application 17577187
Numéro de brevet 11922308
Statut Délivré - en vigueur
Date de dépôt 2022-01-17
Date de la première publication 2022-10-06
Date d'octroi 2024-03-05
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Leskovec, Jurij
  • Eksombatchai, Chantat
  • Chen, Kaifeng
  • He, Ruining
  • Ying, Rex

Abrégé

Systems and methods for generating embeddings for nodes of a corpus graph are presented. More particularly, operations for generation of an aggregated embedding vector for a target node is efficiently divided among operations on a central processing unit and operations on a graphic processing unit. With regard to a target node within a corpus graph, processing by one or more central processing units (CPUs) is conducted to identify the target node's relevant neighborhood (of nodes) within the corpus graph. This information is prepared and passed to one or more graphic processing units (GPUs) that determines the aggregated embedding vector for the target node according to data of the relevant neighborhood of the target node.

Classes IPC  ?

  • G06N 3/08 - Méthodes d'apprentissage
  • G06F 9/38 - Exécution simultanée d'instructions, p. ex. pipeline ou lecture en mémoire
  • G06F 16/182 - Systèmes de fichiers distribués
  • G06F 16/22 - IndexationStructures de données à cet effetStructures de stockage
  • G06F 16/51 - IndexationStructures de données à cet effetStructures de stockage
  • G06F 16/901 - IndexationStructures de données à cet effetStructures de stockage
  • G06F 16/9035 - Filtrage basé sur des données supplémentaires, p. ex. sur des profils d'utilisateurs ou de groupes
  • G06F 16/906 - GroupementClassement
  • G06F 16/9535 - Adaptation de la recherche basée sur les profils des utilisateurs et la personnalisation
  • G06F 16/9536 - Personnalisation de la recherche basée sur le filtrage social ou collaboratif
  • G06F 18/211 - Sélection du sous-ensemble de caractéristiques le plus significatif
  • G06F 18/214 - Génération de motifs d'entraînementProcédés de Bootstrapping, p. ex. ”bagging” ou ”boosting”
  • G06F 18/2413 - Techniques de classification relatives au modèle de classification, p. ex. approches paramétriques ou non paramétriques basées sur les distances des motifs d'entraînement ou de référence
  • G06N 3/04 - Architecture, p. ex. topologie d'interconnexion
  • G06N 20/00 - Apprentissage automatique
  • G06V 30/196 - Reconnaissance utilisant des moyens électroniques utilisant des comparaisons successives des signaux d’images avec plusieurs références

86.

Efficient LSH computation

      
Numéro d'application 16417479
Numéro de brevet 11442914
Statut Délivré - en vigueur
Date de dépôt 2019-05-20
Date de la première publication 2022-09-13
Date d'octroi 2022-09-13
Propriétaire Pinterest, Inc. (USA)
Inventeur(s) Kulikov, Vitaliy

Abrégé

Systems and methods are presented for efficient and effective computation of LSH hashing functions for use in various environments, including nearest-neighbor search. A corpus of items is maintained, with each item of the corpus being associated with information identifying one of a plurality of LSH partitions to which the item has been mapped or hashed. In response to an input item, the input item is projected one or more times into an orthoplex inscribed within a multi-dimensional space. For each mapping, a determination is made as to the nearest vertex of the orthoplex to the projected input item, and the LSH partitions associated with the nearest vertex are aggregated and associated with the input item as the input item's LSH partition.

Classes IPC  ?

  • G06F 16/22 - IndexationStructures de données à cet effetStructures de stockage
  • G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet

87.

S SHUFFLES

      
Numéro de série 97588003
Statut En instance
Date de dépôt 2022-09-12
Propriétaire Pinterest, Inc. ()
Classes de Nice  ?
  • 38 - Services de télécommunications
  • 09 - Appareils et instruments scientifiques et électriques
  • 42 - Services scientifiques, technologiques et industriels, recherche et conception
  • 45 - Services juridiques; services de sécurité; services personnels pour individus

Produits et services

electronic bulletin board services downloadable computer software, namely, software that allows users to interact online with information and media content that other users share, and software that allows users to discover, access and share information about, and media content concerning, goods, services, and experiences; downloadable computer software and downloadable software applications that enable electronic communications network users to create, upload, bookmark, view, annotate, and share data, information and media content; software, downloadable and prerecorded, in the nature of a mobile application that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; software downloadable via electronic communications networks and wireless devices that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; downloadable software for facilitating business promotion and connecting social network users with businesses; downloadable electronic publications in the nature of blogs, photographs, and graphic art reproductions in the field of audio visual, visual arts, pictures, graphics, and photography; downloadable computer e-commerce software to allow users to perform electronic business transactions via a global computer network platform as a service (PAAS) featuring computer software platforms that enables internet users to create, upload, bookmark, view, annotate, share and discover data, information and multimedia content; computer services, namely, creating an online community for registered users to participate in discussions, get feedback from their peers, form virtual communities, and engage in social networking services in the field of audio visual, visual arts, pictures, graphics, and photography; providing a website featuring non-downloadable software that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; platform as a service (PAAS) featuring computer software platforms that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; hosting an interactive platform and online non-downloadable software for uploading, posting, showing, displaying, tagging, sharing and transmitting messages, comments, multimedia content, photos, pictures, images, text, information, and other user-generated content; developing and hosting a server on a global computer network for the purpose of facilitating e-commerce via such a server; platform as a service (PAAS) featuring computer software platforms for mobile device communication, namely, providing non-downloadable software that facilitates sharing and discovering information and media content via mobile devices; platform as a service (PAAS) featuring computer software platforms for networked communications, namely, providing non-downloadable software that facilitates sharing and discovering information and media content via local and global computer, mobile, cellular, electronic, wireless, and data communications networks providing online social networking services for purposes of commentary, comparison, collaboration, consultation, evaluation, advice, discussion, research, notification, reporting, identification, information sharing, indexing, information location, entertainment, and pleasure

88.

S

      
Numéro de série 97588011
Statut En instance
Date de dépôt 2022-09-12
Propriétaire Pinterest, Inc. ()
Classes de Nice  ?
  • 38 - Services de télécommunications
  • 09 - Appareils et instruments scientifiques et électriques
  • 35 - Publicité; Affaires commerciales
  • 42 - Services scientifiques, technologiques et industriels, recherche et conception
  • 45 - Services juridiques; services de sécurité; services personnels pour individus

Produits et services

electronic bulletin board services downloadable computer software, namely, software that allows users to interact online with information and media content that other users share, and software that allows users to discover, access and share information about, and media content concerning, goods, services, and experiences; downloadable computer software and downloadable software applications that enable electronic communications network users to create, upload, bookmark, view, annotate, and share data, information and media content; software, downloadable and prerecorded, in the nature of a mobile application that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; software downloadable via electronic communications networks and wireless devices that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; downloadable software for facilitating business promotion and connecting social network users with businesses; downloadable electronic publications in the nature of blogs, photographs, and graphic art reproductions in the field of audio visual, visual arts, pictures, graphics, and photography; downloadable computer e-commerce software to allow users to perform electronic business transactions via a global computer network advertising and promotional services; advertising and marketing services, namely, promoting the products and services of others; business data analysis; business monitoring and consulting services, namely, business data analysis and behavior analysis in the nature of marketing research to provide strategy, insight, and marketing guidance, and for analyzing, understanding and predicting behavior and motivations, and market trends; promoting the goods and services of others by means of operating an online platform with hyperlinks to the online resources of others; providing an online searchable database featuring a wide variety of consumer, business, and industrial goods of others; electronic commerce services, namely, providing information about products via telecommunication networks for advertising and sales purposes platform as a service (PAAS) featuring computer software platforms that enables internet users to create, upload, bookmark, view, annotate, share and discover data, information and multimedia content; computer services, namely, creating an online community for registered users to participate in discussions, get feedback from their peers, form virtual communities, and engage in social networking services in the field of audio visual, visual arts, pictures, graphics, and photography; providing a website featuring non-downloadable software that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; platform as a service (PAAS) featuring computer software platforms that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; hosting an interactive platform and online non-downloadable software for uploading, posting, showing, displaying, tagging, sharing and transmitting messages, comments, multimedia content, photos, pictures, images, text, information, and other user-generated content; developing and hosting a server on a global computer network for the purpose of facilitating e-commerce via such a server; platform as a service (PAAS) featuring computer software platforms for mobile device communication, namely, providing non-downloadable software that facilitates sharing and discovering information and media content via mobile devices; platform as a service (PAAS) featuring computer software platforms for networked communications, namely, providing non-downloadable software that facilitates sharing and discovering information and media content via local and global computer, mobile, cellular, electronic, wireless, and data communications networks providing online social networking services for purposes of commentary, comparison, collaboration, consultation, evaluation, advice, discussion, research, notification, reporting, identification, information sharing, indexing, information location, entertainment, and pleasure

89.

S

      
Numéro de série 97588015
Statut Enregistrée
Date de dépôt 2022-09-12
Date d'enregistrement 2024-01-02
Propriétaire Pinterest, Inc. ()
Classes de Nice  ? 09 - Appareils et instruments scientifiques et électriques

Produits et services

downloadable software applications that enable electronic communications network users to create, upload, bookmark, view, annotate, and share data, information and media content; software, downloadable and prerecorded, in the nature of a mobile application that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; software downloadable via electronic communications networks and wireless devices that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content

90.

SHUFFLES

      
Numéro de série 97583874
Statut Enregistrée
Date de dépôt 2022-09-08
Date d'enregistrement 2024-01-02
Propriétaire Pinterest, Inc. ()
Classes de Nice  ? 09 - Appareils et instruments scientifiques et électriques

Produits et services

downloadable software applications that enable electronic communications network users to create, upload, bookmark, view, annotate, and share data, information and media content; software, downloadable and prerecorded, in the nature of a mobile application that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; software downloadable via electronic communications networks and wireless devices that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content

91.

SHUFFLES

      
Numéro de série 97583816
Statut En instance
Date de dépôt 2022-09-08
Propriétaire Pinterest, Inc. ()
Classes de Nice  ?
  • 38 - Services de télécommunications
  • 09 - Appareils et instruments scientifiques et électriques
  • 42 - Services scientifiques, technologiques et industriels, recherche et conception
  • 45 - Services juridiques; services de sécurité; services personnels pour individus

Produits et services

electronic bulletin board services downloadable computer software, namely, software that allows users to interact online with information and media content that other users share, and software that allows users to discover, access and share information about, and media content concerning, goods, services, and experiences; downloadable computer software and downloadable software applications that enable electronic communications network users to create, upload, bookmark, view, annotate, and share data, information and media content; software, downloadable and prerecorded, in the nature of a mobile application that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; software downloadable via electronic communications networks and wireless devices that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; downloadable software for facilitating business promotion and connecting social network users with businesses; downloadable electronic publications in the nature of blogs, photographs, and graphic art reproductions in the field of audio visual, visual arts, pictures, graphics, and photography; downloadable computer e-commerce software to allow users to perform electronic business transactions via a global computer network platform as a service (PAAS) featuring computer software platforms that enables internet users to create, upload, bookmark, view, annotate, share and discover data, information and multimedia content; computer services, namely, creating an online community for registered users to participate in discussions, get feedback from their peers, form virtual communities, and engage in social networking services in the field of audio visual, visual arts, pictures, graphics, and photography; providing a website featuring non-downloadable software that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; platform as a service (PAAS) featuring computer software platforms that enables electronic communications network users to create, upload, bookmark, view, annotate, share and discover data, information and media content; hosting an interactive platform and online non-downloadable software for uploading, posting, showing, displaying, tagging, sharing and transmitting messages, comments, multimedia content, photos, pictures, images, text, information, and other user-generated content; developing and hosting a server on a global computer network for the purpose of facilitating e-commerce via such a server; platform as a service (PAAS) featuring computer software platforms for mobile device communication, namely, providing non-downloadable software that facilitates sharing and discovering information and media content via mobile devices; platform as a service (PAAS) featuring computer software platforms for networked communications, namely, providing non-downloadable software that facilitates sharing and discovering information and media content via local and global computer, mobile, cellular, electronic, wireless, and data communications networks providing online social networking services for purposes of commentary, comparison, collaboration, consultation, evaluation, advice, discussion, research, notification, reporting, identification, information sharing, indexing, information location, entertainment, and pleasure

92.

Probabilistic determination of compatible content

      
Numéro d'application 17827359
Numéro de brevet 12112365
Statut Délivré - en vigueur
Date de dépôt 2022-05-27
Date de la première publication 2022-09-08
Date d'octroi 2024-10-08
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Johnson, Brian
  • Milinovich, John
  • Riedel, Lance Alan
  • Look, Andrew
  • Narasimhan, Mukund
  • Liu, Yu

Abrégé

According to aspects of the disclosed subject matter, a taste graph comprising likely content collection nodes with corresponding likely digital content items is generated through one or more analyses of a corpus of content collections that is maintained by the online content service. As should be understood, this corpus of content collections is comprised of a plurality of curated content collections, with each content collection comprising a plurality of digital content items. With this taste graph available, as a user generates (or in response to a user generating) a content collection of digital content items, reference can be made to the taste graph to identify one or more digital content items that may be added to the content collection, where the one or more digital content items have a probabilistic likelihood of being complimentary and/or compatible with the other digital content items of the content collection.

Classes IPC  ?

  • G06Q 30/06 - Transactions d’achat, de vente ou de crédit-bail
  • G06F 16/957 - Optimisation de la navigation, p. ex. mise en cache ou distillation de contenus
  • G06Q 30/0201 - Modélisation du marchéAnalyse du marchéCollecte de données du marché
  • G06Q 30/0282 - Notation ou évaluation d’opérateurs commerciaux ou de produits
  • G06Q 30/0601 - Commerce électronique [e-commerce]
  • G06Q 50/00 - Technologies de l’information et de la communication [TIC] spécialement adaptées à la mise en œuvre des procédés d’affaires d’un secteur particulier d’activité économique, p. ex. aux services d’utilité publique ou au tourisme

93.

Estimating conversions

      
Numéro d'application 17748719
Numéro de brevet 11907962
Statut Délivré - en vigueur
Date de dépôt 2022-05-19
Date de la première publication 2022-09-01
Date d'octroi 2024-02-20
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Mccurdy, Sean R.
  • Fang, Zheng
  • Bhansali, Rohil

Abrégé

An online host for conducting a promotion campaign is presented. Online behaviors of subscribers exposed by the promotion campaign are tracked for determining conversion counts for the promotion campaign. For exposed subscribers whose online behaviors are not sufficiently available to the online host to determine conversion counts (non-measurable subscribers), a machine learning model is trained to predict conversion counts based on online behaviors that are conducted on internet locations under control of the online service, and further trained to determine an estimated error rate regarding the predicted conversion counts. Conversion counts for a promotion campaign are determined according to an analysis of the online behaviors of the exposed subscribers whose online behaviors are sufficiently available to the online host to determine conversion counts (measurable subscribers), and according to the predicted conversion counts of the non-measurable subscribers with an estimated error rate that meets or exceeds a predetermined threshold.

Classes IPC  ?

  • G06Q 30/0201 - Modélisation du marchéAnalyse du marchéCollecte de données du marché
  • G06Q 30/0242 - Détermination de l’efficacité des publicités
  • G06Q 30/0241 - Publicités
  • G06N 20/00 - Apprentissage automatique
  • G06Q 30/0272 - Période d’exposition à la publicité
  • G06F 18/214 - Génération de motifs d'entraînementProcédés de Bootstrapping, p. ex. ”bagging” ou ”boosting”

94.

Methods of and systems for searching by incorporating user-entered information

      
Numéro d'application 17732407
Numéro de brevet 11693864
Statut Délivré - en vigueur
Date de dépôt 2022-04-28
Date de la première publication 2022-08-11
Date d'octroi 2023-07-04
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Tanne, Michael
  • Lu, Yunshan
  • Karsh, Bruce D.

Abrégé

A system for and a method of using user-entered information to return more meaningful information in response to Internet search queries are disclosed. A method in accordance with the disclosed subject matter comprises managing a database in response to multiple user inputs and displaying search results from the database in response to a search query. The search results include a results list and supplemental data related to the search query. Managing the database includes, among other things, re-ranking elements in the results list, storing information related to relevancies of elements in the results list, blocking a link in the results list, storing links to documents related to the search query, or any combination of these. The supplemental data include descriptions of or indices to one or more concepts related to the search query.

Classes IPC  ?

  • G06F 16/00 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet
  • G06F 16/2457 - Traitement des requêtes avec adaptation aux besoins de l’utilisateur
  • G06F 16/951 - IndexationTechniques d’exploration du Web
  • G06F 16/332 - Formulation de requêtes
  • G06F 16/9535 - Adaptation de la recherche basée sur les profils des utilisateurs et la personnalisation
  • G06F 40/134 - Création de liens hypertexte
  • G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p. ex. des menus

95.

Recommending content to subscribers

      
Numéro d'application 16909894
Numéro de brevet 11409821
Statut Délivré - en vigueur
Date de dépôt 2020-06-23
Date de la première publication 2022-08-09
Date d'octroi 2022-08-09
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Pal, Aditya
  • Eksombatchai, Chantat
  • Zhou, Yitong
  • Zhao, Bo
  • Rosenberg, Charles Joseph
  • Leskovec, Jurij

Abrégé

Systems and methods for recommending content to an online service subscriber are presented. For each subscriber, content items that were the subject of the subscriber's prior interactions are projected, via associated embedding vectors, into a content item embedding space. The content items, via their projections into the content item embedding space, are clustered to form a plurality of interest clusters for the subscriber. A representative embedding vector is determined for each interest cluster, and a plurality of these embedding vectors are stored as the representative embedding vectors for the subscriber. The online service, in response to a request for recommended content for a subscriber, selects a first representative embedding vector associated with the subscriber and identifies a new content item from a corpus of content items according to a similarity measure between the first representative embedding vector and an embedding vector associated with the new content item.

Classes IPC  ?

  • G06F 16/9535 - Adaptation de la recherche basée sur les profils des utilisateurs et la personnalisation
  • G06F 16/906 - GroupementClassement

96.

Content presentation

      
Numéro d'application 17208737
Numéro de brevet 11403360
Statut Délivré - en vigueur
Date de dépôt 2021-03-22
Date de la première publication 2022-08-02
Date d'octroi 2022-08-02
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Lu, Wendy
  • Velo, Justin
  • Tow, Kelvin
  • You, Mengya
  • Crawford, Nicole
  • He, Harrison

Abrégé

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing content. One of the methods includes providing a plurality of image content items to an application interface of a client device for presentation; receiving a user selection of a particular image content item of the plurality of presented image content items; and responsive to the selection, providing a combination of native content and third party content associated with the selected image content item, wherein the native content includes a close up view of the selected image content item and the third party content includes a third party webpage.

Classes IPC  ?

  • G06F 17/00 - Équipement ou méthodes de traitement de données ou de calcul numérique, spécialement adaptés à des fonctions spécifiques
  • G06F 16/954 - Navigation, p. ex. en utilisant la navigation par catégories
  • G06F 3/0485 - Défilement ou défilement panoramique
  • G06F 3/04845 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs pour la transformation d’images, p. ex. glissement, rotation, agrandissement ou changement de couleur
  • G06F 16/54 - NavigationVisualisation à cet effet
  • G06F 16/957 - Optimisation de la navigation, p. ex. mise en cache ou distillation de contenus

97.

Computer-readable storage medium for presenting object identifiers for real world objects on wearable and portable devices

      
Numéro d'application 14660793
Numéro de brevet 11386479
Statut Délivré - en vigueur
Date de dépôt 2015-03-17
Date de la première publication 2022-07-12
Date d'octroi 2022-07-12
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Gavini, Naveen
  • Wilson, Jason Luke
  • Sharp, Evan

Abrégé

This application describes a system and process for providing object identifiers relating to real world objects to users based on the location of the user and the anticipated interested of the user in an object within a defined distance of the user. For example, if the user is within a retail store, a portable device associated with the user may detect or receive a beacon transmitted from a location within the retail store and object identifiers representative of objects within the store may be generated and provided to the user. In some implementations, only object identifier representative of items determined to be of likely interest to the user may be provided for presentation to the user.

Classes IPC  ?

  • G06Q 30/06 - Transactions d’achat, de vente ou de crédit-bail
  • H04W 4/02 - Services utilisant des informations de localisation

98.

Visual search refinement

      
Numéro d'application 17698961
Numéro de brevet 11714865
Statut Délivré - en vigueur
Date de dépôt 2022-03-18
Date de la première publication 2022-06-30
Date d'octroi 2023-08-01
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Wilson, Jason Luke
  • Gavini, Naveen

Abrégé

Described is a system and method for enabling visual search for information. With each selection of a search term, additional search terms are dynamically selected and presented to the user in conjunction with results matching the currently selected search terms. Likewise, a selected search term may be tokenized and a graphical token presented to the user to represent the selected search term.

Classes IPC  ?

  • G06F 16/00 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet
  • G06F 16/9535 - Adaptation de la recherche basée sur les profils des utilisateurs et la personnalisation

99.

Probabilistic determination of compatible content

      
Numéro d'application 15957822
Numéro de brevet 11373230
Statut Délivré - en vigueur
Date de dépôt 2018-04-19
Date de la première publication 2022-06-28
Date d'octroi 2022-06-28
Propriétaire Pinterest, Inc. (USA)
Inventeur(s)
  • Johnson, Brian
  • Milinovich, John
  • Riedel, Lance Alan
  • Look, Andrew
  • Narasimhan, Mukund
  • Liu, Yu

Abrégé

According to aspects of the disclosed subject matter, a taste graph comprising likely content collection nodes with corresponding likely digital content items is generated through one or more analyses of a corpus of content collections that is maintained by the online content service. As should be understood, this corpus of content collections is comprised of a plurality of curated content collections, with each content collection comprising a plurality of digital content items. With this taste graph available, as a user generates (or in response to a user generating) a content collection of digital content items, reference can be made to the taste graph to identify one or more digital content items that may be added to the content collection, where the one or more digital content items have a probabilistic likelihood of being complimentary and/or compatible with the other digital content items of the content collection.

Classes IPC  ?

  • G06Q 30/06 - Transactions d’achat, de vente ou de crédit-bail
  • G06F 16/957 - Optimisation de la navigation, p. ex. mise en cache ou distillation de contenus
  • G06Q 30/02 - MarketingEstimation ou détermination des prixCollecte de fonds
  • G06N 7/00 - Agencements informatiques fondés sur des modèles mathématiques spécifiques
  • G06Q 50/00 - Technologies de l’information et de la communication [TIC] spécialement adaptées à la mise en œuvre des procédés d’affaires d’un secteur particulier d’activité économique, p. ex. aux services d’utilité publique ou au tourisme

100.

Order management systems and methods

      
Numéro d'application 17127910
Numéro de brevet 11893620
Statut Délivré - en vigueur
Date de dépôt 2020-12-18
Date de la première publication 2022-06-23
Date d'octroi 2024-02-06
Propriétaire PINTEREST, INC. (USA)
Inventeur(s)
  • Rodriguez, Jorge
  • Zhou, Xinyi
  • Grunewald, James
  • Aggarwal, Amit
  • Zaytsev, Andrey
  • Gilfanov, Ruslan

Abrégé

Example order management systems and methods are described. In one implementation, a catalog ingestion system receives data associated with multiple products offered by multiple brands. A commerce management system receives a customer order from a customer. The customer order includes at least a portion of the multiple products offered by the multiple brands. The commerce management system splits the customer order into multiple brand orders such that each brand order is associated with products in the customer order from a particular brand. An integration platform fulfills the brand orders by submitting the brand orders to the associated brands.

Classes IPC  ?

  • G06Q 30/06 - Transactions d’achat, de vente ou de crédit-bail
  • G06Q 10/107 - Gestion informatisée du courrier électronique
  • G06Q 10/08 - Logistique, p. ex. entreposage, chargement ou distributionGestion d’inventaires ou de stocks
  • G06Q 20/08 - Architectures de paiement
  • H04L 51/42 - Aspects liés aux boîtes aux lettres, p. ex. synchronisation des boîtes aux lettres
  • G06Q 30/0601 - Commerce électronique [e-commerce]
  • G06Q 10/087 - Gestion d’inventaires ou de stocks, p. ex. exécution des commandes, approvisionnement ou régularisation par rapport aux commandes
  • G06Q 10/0837 - Transactions de retour
  • G06Q 10/083 - Expédition
  • G06F 9/445 - Chargement ou démarrage de programme
  • G06Q 10/0833 - Repérage
  • G06F 9/44 - Dispositions pour exécuter des programmes spécifiques
  • H04L 101/37 - Adresses courriel
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