A system receives a query from a user specifying a geographic location at which the user wishes to obtain data relating to travel experiences. The system obtains a first score associated with a first travel experience and a second score associated with a second travel experience, the first score being different than the second. A score is based on at least one quality indicator of the experience. The system defines a plurality of differently-located virtual boundaries around the travel location, each successive boundary indicating an area located at a greater distance from the travel location. The system then displays to the user a list of experiences, wherein the experiences are rank-ordered before presentation to the user. The rank ordering of experiences is dependent on both the virtual boundary into which the experience falls and the score associated with the experience.
System receives request from user for decision making options, and provide gameplan document that suggests accessing first and second data source to collect options. System extracts first data records set from content copied by user from first data source, and inserts first data records set in first table in gameplan document. System extracts second data records set from content copied by user from second data source, and inserts second data records set in second table in gameplan document. System inserts combined data records set, based on first data records set joined with second data records set, in combined data table in gameplan document. System enables user to identify candidates, for options, in combined data records set in response to user commands. System determines overall scores corresponding to candidates, based on applying criteria, scored by user, to each candidate. System outputs candidates, ranked based on corresponding scores, as decision making options.
A system is described for allowing a user to communicate with an agent of a listing network platform. The system receives, by a network site, a user interaction in a communication session with an agent of a listing network platform. The system analyzes, by a first machine learning model, a profile associated with the user on the listing network platform to predict a subset of information that is relevant to the user interaction with the communication session. The system combines the subset of information into a prompt and processes the prompt by a generative machine learning model to generate a message that responds to the user interaction. The system, in response to receiving the user interaction, presents the message by the agent of the listing network platform to the user in a user interface of the listing network platform.
A system is described for allowing a user to communicate with an agent of a listing network platform. The system receives, by a network site, a user interaction in a communication session with an agent of a listing network platform. The system analyzes, by a first machine learning model, a profile associated with the user on the listing network platform to predict a subset of information that is relevant to the user interaction with the communication session. The system combines the subset of information into a prompt and processes the prompt by a generative machine learning model to generate a message that responds to the user interaction. The system, in response to receiving the user interaction, presents the message by the agent of the listing network platform to the user in a user interface of the listing network platform.
Systems and methods herein describe generating a mixture of experts (MoE) models for image classification. The systems and methods include training a plurality of neural network models as experts, wherein the experts are trained to predict an image class, to predict amenities present in the image, to predict location categories in the image, or a combination thereof The system and methods additionally include training experts based on input differentiation. The system and methods also include training experts having different model architectures or variants of model architectures, and combining the trained experts into an ensemble model. The ensemble model can then be used to classify new images.
G06V 10/80 - Fusion, c.-à-d. combinaison des données de diverses sources au niveau du capteur, du prétraitement, de l’extraction des caractéristiques ou de la classification
Systems and methods herein describe generating a mixture of experts (MoE) models for image classification. The systems and methods include training a plurality of neural network models as experts, wherein the experts are trained to predict an image class, to predict amenities present in the image, to predict location categories in the image, or a combination thereof. The system and methods additionally include training experts based on input differentiation. The system and methods also include training experts having different model architectures or variants of model architectures, and combining the trained experts into an ensemble model. The ensemble model can then be used to classify new images.
G06V 10/80 - Fusion, c.-à-d. combinaison des données de diverses sources au niveau du capteur, du prétraitement, de l’extraction des caractéristiques ou de la classification
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
14.
Display screen of a programmed computer system with graphical user interface
Methods and systems that organize images for accommodation listings are described. The methods and systems present, in a graphical user interface (GUI), an option to arrange the plurality of images according to classifications associated with the plurality of images. The methods and systems, in response to receiving input that selects the option, animate in the GUI a subset of the plurality of images as being shuffled into one or more of the classifications and, after the subset of the plurality of images are animated for a specified threshold period of time, present in the GUI a template comprising a plurality of regions each associated with a different classification. The methods and systems populate regions of the plurality of regions associated with different classifications with respective images that correspond to the classifications.
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
A computer-implemented method includes receiving a task performance request; retrieving a stored task specification corresponding to the task performance request; generating a task implementation request including the stored task specification and an execution context; generating a task implementation corresponding to the task implementation request, the task implementation including a sequence of task execution commands; and causing execution of the sequence of task execution commands.
An embodiment includes training a first large language model (LLM) to generate source code implementing an input set of user interface (UI) components, the training resulting in a trained UI generation model. An embodiment includes generating, from a first decision query, a first UI generation task, the first UI generation task comprising a decision criterion and a dataset. An embodiment includes generating, from the first UI generation task, using the trained UI generation model, first source code implementing a first arrangement of UI components. An embodiment includes executing, using a webpage rendering framework, the first source code, the executing rendering the first arrangement of UI components onto a webpage.
A computer-implemented method includes receiving a task performance request; retrieving a stored task specification corresponding to the task performance request; generating a task implementation request including the stored task specification and an execution context; generating a task implementation corresponding to the task implementation request, the task implementation including a sequence of task execution commands; and causing execution of the sequence of task execution commands.
An embodiment includes training a first large language model (LLM) to generate source code implementing an input set of user interface (UI) components, the training resulting in a trained UI generation model. An embodiment includes generating, from a first decision query, a first UI generation task, the first UI generation task comprising a decision criterion and a dataset. An embodiment includes generating, from the first UI generation task, using the trained UI generation model, first source code implementing a first arrangement of UI components. An embodiment includes executing, using a webpage rendering framework, the first source code, the executing rendering the first arrangement of UI components onto a webpage.
A session shared data system accesses a first communication between a user and a support agent on a first communication channel and stores communication data associated with the first communication in a session shared data object. The session shared data system accesses a subsequent communication between the user and a second agent on a second communication channel, receives a query associated with the subsequent communication and transmits the response to a device of the second agent.
A session shared data system accesses a first communication between a user and a support agent on a first communication channel and stores communication data associated with the first communication in a session shared data object. The session shared data system accesses a subsequent communication between the user and a second agent on a second communication channel, receives a query associated with the subsequent communication and transmits the response to a device of the second agent.
A system receives a query from a user specifying a geographic location at which the user wishes to obtain data relating to travel experiences. The system obtains a first score associated with a first travel experience and a second score associated with a second travel experience, the first score being different than the second. A score is based on at least one quality indicator of the experience. The system defines a plurality of differently-located virtual boundaries around the travel location, each successive boundary indicating an area located at a greater distance from the travel location. The system then displays to the user a list of experiences, wherein the experiences are rank-ordered before presentation to the user. The rank ordering of experiences is dependent on both the virtual boundary into which the experience falls and the score associated with the experience.
Systems and methods are provided to classify activities into clusters. The systems and methods access data representing activity on a network site and generate, based on the data, a plurality of feature sets representing periods of activeness on the network side. The systems and methods form a subset of the plurality of feature sets by reducing dimensionality of the plurality of feature sets. The systems and methods generate a plurality of clusters of the subset of the plurality of feature sets, each cluster being associated with a label representing a different type of activeness on the network site, and generate a database query set based on the plurality of clusters and the plurality of feature sets to classify one or more activities on the network site into one of the plurality of clusters.
Systems and methods are provided to generate an actual number of search results, a total estimated number of search results based on historical search data in the online marketplace, and a conversion estimated number of search results for users who converted, for a given set of query parameters in an online marketplace. The systems and methods generates a low inventory state metrics based on determining a first probability of getting the actual number of search results plus one given the conversion number of search results, a second probability of getting the actual number of results given the total estimated number of search results, a third probability of getting the actual number of search results given the conversion number of search results and a fourth probability of getting the actual number of search results plus one given the total estimated number of search results
Systems and methods described herein retrieve data from a data store, the data comprising marketing data associated with a plurality of advertising channels disposed in a plurality of geographic units. The systems and methods pre-process the data to derive a pre-processed data set, and hierarchically cluster the pre-processed data set. The systems and methods further derive a reduced multicollinearity data set having one or more clusters based on the hierarchically clustering by reducing a distance metric among geographic units of the plurality of geographic units that are disposed inside the one or more clusters, and analyze the one or more clusters with a model to generate one or more visualizations used to increase an impression impact, increase a carryover, or a combination thereof, in at least one of the plurality of advertising channels.
Systems and methods are provided to generate a set of vector representations for each word of a plurality of words in a set of social media data by inputting each word into each of a predefined number of machine learning models to output each of the set of vector representations, the set of social media data comprising social media data from a plurality of social network platforms in a predefined window of time. The systems and methods further provide for generating a similarity score for each vector representation in the set of vector representations for each word output from the predefined number of machine learning models with respect to a given brand name, and generating a perception score for each word based on the generated similarity score for each vector representation in the set of vector representations for each word.
G06F 40/58 - Utilisation de traduction automatisée, p. ex. pour recherches multilingues, pour fournir aux dispositifs clients une traduction effectuée par le serveur ou pour la traduction en temps réel
A cost-focused determination of whether to deliver an electronic advertisement or notice to a particular user can be made through a cumulative consideration of the predicted return on investment over each of a plurality of electronic channels. A plurality of channel-specific budget values are calculated for the user, one for each channel, each setting an upper spending limit for advertisement to the user over that channel based on the user's information and their activity on the channel. A global budget is calculated for the user using a weighted aggregation of the channel-specific values, information about the user and their activity with the advertiser, and consideration of “overlap” effects of advertising to the same user on several channels. When managing whether to deliver an advertisement over a channel, if the channel-specific value is lower than the global budget, the advertisement is delivered, and the global budget is decreased by a complementary amount.
A method is provided for organizing wish lists in an online marketplace. The method includes displaying, on a wish list management graphical user interface, category affordances corresponding to properties available in the online marketplace. In response to detecting an input from a user to select a category affordance, the method includes displaying property cards. Each property card corresponds to properties for a category corresponding to the category affordance. The method also includes displaying wish list icons. Each wish list icon corresponds to a respective property card. In response to detecting a selection of a wish list icon, the method includes generating a wish list for the category and associating a property corresponding to the wish list icon with a wish list for the category. In response to detecting the user selecting an option to view a wish list, the method includes displaying one or more properties of a wish list.
A system that enables synchronized interaction between voice input and a visual user interface is described. The system receives, by a network site via a first user interaction channel, a user request to perform an action with a listing network platform. The system establishes, by the network site, a session associated with a session identifier for the user request and provides an option for the user to continue interacting with the listing network platform through a second user interaction channel. The system, in response to receiving input that selects the option, uses the session identifier associated with the session to synchronize a first set of inputs received through the first user interaction channel with a second set of inputs received through the second user interaction channel to complete the action on the listing network platform.
A method is provided for host management in an online marketplace. The method includes obtaining a property listing listed on the online marketplace. The method may also include providing a host management graphical user interface for managing co-hosts. If the property listing is associated with one or more co-hosts, the method includes displaying host detail affordances. In response to detecting a user selecting a host detail affordance corresponding to a co-host, the method includes displaying permissions, payouts, and activity log, for the co-host. If the property listing is not associated with co-hosts, the method includes displaying a co-host add option to add a co-host for the property listing. The method may also include, in response to detecting an input from the user, to select the co-host add option, allowing the user to specify a new co-host and associating the new co-host with the property listing.
A system that enables synchronized interaction between voice input and a visual user interface is described. The system receives, by a network site via a first user interaction channel, a user request to perform an action with a listing network platform. The system establishes, by the network site, a session associated with a session identifier for the user request and provides an option for the user to continue interacting with the listing network platform through a second user interaction channel. The system, in response to receiving input that selects the option, uses the session identifier associated with the session to synchronize a first set of inputs received through the first user interaction channel with a second set of inputs received through the second user interaction channel to complete the action on the listing network platform.
Systems and methods herein describe ranking reviews that specify details of a host user. The described systems and methods access a set of reviews associated with a host user and listing data, and for each review in the set of reviews, generate a first relevancy score associated with the host user and a second relevancy score associated with the listing data using a transformer machine learning model, determine a first rank score for the review based on the first relevancy score. The systems and methods cause display of the set of reviews in an order based on the associated first rank score on a graphical user interface of a computing device.
A method is provided for host management in an online marketplace. The method includes obtaining a property listing listed on the online marketplace. The method may also include providing a host management graphical user interface for managing co-hosts. If the property listing is associated with one or more co-hosts, the method includes displaying host detail affordances. In response to detecting a user selecting a host detail affordance corresponding to a co-host, the method includes displaying permissions, payouts, and activity log, for the co-host. If the property listing is not associated with co-hosts, the method includes displaying a co-host add option to add a co-host for the property listing. The method may also include, in response to detecting an input from the user, to select the co-host add option, allowing the user to specify a new co-host and associating the new co-host with the property listing.
A method is provided for organizing wish lists in an online marketplace. The method includes displaying, on a wish list management graphical user interface, category affordances corresponding to properties available in the online marketplace. In response to detecting an input from a user to select a category affordance, the method includes displaying property cards. Each property card corresponds to properties for a category corresponding to the category affordance. The method also includes displaying wish list icons. Each wish list icon corresponds to a respective property card. In response to detecting a selection of a wish list icon, the method includes generating a wish list for the category and associating a property corresponding to the wish list icon with a wish list for the category. In response to detecting the user selecting an option to view a wish list, the method includes displaying one or more properties of a wish list.
A system that enables searching for representing listings for accommodation reservations on a map is described. The system receives, by a network site of a listing network platform, input comprising search criteria associated with a geographical region and identifies a plurality of listings matching the search criteria. The system identifies a first subset listings of the plurality of listings that is each associated with a respective location that is within a boundary associated with the geographical region and a second subset listings of the plurality of listings that is each associated with a respective location that is outside the boundary associated with the geographical region. The system visually distinguishes the first subset of listings from the second subset of listings on a map-based graphical user interface (GUI) that represents the plurality of listings matching the search criteria.
G06F 3/04817 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect utilisant des icônes
G06F 3/04842 - Sélection des objets affichés ou des éléments de texte affichés
G06F 16/25 - Systèmes d’intégration ou d’interfaçage impliquant les systèmes de gestion de bases de données
50.
CROSS-LISTED PROPERTY MATCHING USING IMAGE DESCRIPTOR FEATURES
Two sets of data, each containing property listings, are obtained from two discrete merchant platforms. Each property listing in a set of data of a first merchant is sequentially paired with each of the property listings in a set of data of a second merchant. For each pair, each image of the property listing of the first merchant is compared to each image of the property listing of the second merchant, and images of statistically sufficient similarity are identified. The similarity of images, and in particular, of similar images likely to be rooms of the property, are considered in a determination of whether the product listings of the first and second merchant are for the same cross-listed product.
G06F 16/29 - Bases de données d’informations géographiques
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
G06Q 10/02 - Réservations, p. ex. pour billetterie, services ou manifestations
G06Q 30/0201 - Modélisation du marchéAnalyse du marchéCollecte de données du marché
G06V 10/75 - Organisation de procédés de l’appariement, p. ex. comparaisons simultanées ou séquentielles des caractéristiques d’images ou de vidéosApproches-approximative-fine, p. ex. approches multi-échellesAppariement de motifs d’image ou de vidéoMesures de proximité dans les espaces de caractéristiques utilisant l’analyse de contexteSélection des dictionnaires
A system that enables searching for listings for accommodation reservations is described. The system receives, by a network site of a listing network platform, input comprising search criteria and identifies a plurality of listings matching the search criteria. The system generates a graphical user interface comprising a plurality of graphical objects each associated with a respective one of the identified plurality of listings. The system determines that the search criteria satisfies an amenity criterion and, in response, causes one or more amenities associated with an individual listing of the identified plurality of listings to be presented in an individual graphical object of the plurality of graphical objects associated with the individual listing.
A system that enables searching for representing listings for accommodation reservations on a map is described. The system receives, by a network site of a listing network platform, input comprising search criteria associated with a geographical region and identifies a plurality of listings matching the search criteria. The system identifies a first subset listings of the plurality of listings that is each associated with a respective location that is within a boundary associated with the geographical region and a second subset listings of the plurality of listings that is each associated with a respective location that is outside the boundary associated with the geographical region. The system visually distinguishes the first subset of listings from the second subset of listings on a map-based graphical user interface (GUI) that represents the plurality of listings matching the search criteria.
There is provided a method that is performed while a host and a guest are using a conversational messaging interface. For a message thread, in response to receiving a guest message, the method computes a probability for guest issues by inputting feature vectors from the guest message to a guest issue detection model. In response to receiving a host message, the message computes a probability for host issues by inputting feature vectors from the host message to a host issue detection model. If the message thread includes particular keywords, and if the probability for the guest issues is above a guest issue predetermined threshold, the method includes providing alerts that is visible only to the guest. If the probability for the host issues is above a host issue predetermined threshold, the method also includes providing alerts that is visible only to the host.
09 - Appareils et instruments scientifiques et électriques
16 - Papier, carton et produits en ces matières
35 - Publicité; Affaires commerciales
41 - Éducation, divertissements, activités sportives et culturelles
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable software; electronic downloadable publications; downloadable presentations; downloadable audio recordings; podcasts; mobile applications. Printed publications; books. Business consultation services; business management services; business administration services; advertising services; business management consultancy and personnel consultancy in the field of executive and leadership development; advisory services in connection with all the foregoing services. Entertainment services; education services; business education and training services; executive and leadership training services; providing online non-downloadable publications; production of podcasts; conducting lectures, presentations, and workshops. Providing online non-downloadable software; software as a service (SAAS) services; advice and consulting regarding business technology; software as a service (SAAS) services in the fields of business, business consultation and business development.
09 - Appareils et instruments scientifiques et électriques
16 - Papier, carton et produits en ces matières
41 - Éducation, divertissements, activités sportives et culturelles
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Business consultation services; Business management services; Business administration services; Advertising services; Business advice and consulting services regarding executive leadership development; Business advisory services. Downloadable software providing digital content in the fields of business, entrepreneurship, and executive or leadership development; Electronic downloadable publications in the nature of books, magazines, blogs, and newsletters in the fields of business, entrepreneurship, and executive or leadership development; Downloadable presentations in the nature of printable educational and informational materials in the fields of business, entrepreneurship, and executive or leadership development; Downloadable audio recordings featuring digital content on business, entrepreneurship, and executive or leadership development; Downloadable podcasts in the fields of business, entrepreneurship, and executive or leadership development; Downloadable mobile applications, providing digital content in the fields of business, entrepreneurship, and executive or leadership development. Printed publications in the nature of books and magazines in the fields of business, entrepreneurship, and executive or leadership development; Printed books in the fields of business, entrepreneurship, and executive or leadership development. Entertainment services in the nature of hosting social entertainment events; Education services in the nature of providing classes and instruction, lectures, seminars, and webinars in the fields of business, entrepreneurship, and executive or leadership development; Business education in the nature of business, entrepreneurship, and executive or leadership development training services; Executive and leadership business training services; Providing online non-downloadable publications in the nature of books, magazines, blogs, and newsletters in the fields of business, entrepreneurship, and executive or leadership development; production of podcasts; Conducting lectures, presentations, and workshops in the fields of business, entrepreneurship, and executive or leadership development. Providing online non-downloadable software providing digital content in the fields of business, entrepreneurship, and executive or leadership development; Software as a service (SAAS) services in the fields of business, entrepreneurship, and executive or leadership development; Technical advice and consulting regarding business technology; Software as a service (SAAS) services in the fields of business, entrepreneurship, and executive or leadership development for use in the sharing of educational and entertainment content.
A server obtains content in a first language and receives a first request from a first client device to view the content, wherein the first client device is associated with a second language selected by a user operating the first client device. In response to receiving the first request, the server determines that the first language is different from the second language and determines that a storage of the server does not include a machine-translated version of the content in the second language. In accordance with these determinations, the server obtains a machine-translated version of the content in the second language and stores the machine-translated version of the content in the second language in the storage for subsequent requests to view the content in the second language.
G06F 40/58 - Utilisation de traduction automatisée, p. ex. pour recherches multilingues, pour fournir aux dispositifs clients une traduction effectuée par le serveur ou pour la traduction en temps réel
G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p. ex. des menus
Systems and methods are provided to analyze at least one sensor of a computing device to determine that the computing device is in a substantially flat position on the first surface, activate a camera comprising a depth sensor, and detect a second surface in a camera view of the camera. The computing device further analyzes pixel measurements from the depth sensor in a predefined area of the detected second surface to determine a minimum measurement of all of the pixel measurements in the predefined area of the detected surface, causes display of the minimum measurement from the first surface to the second surface overlaid on an image of the first and second surface in the camera view on a user interface of the computing device, and captures an image of the display.
G01B 11/22 - Dispositions pour la mesure caractérisées par l'utilisation de techniques optiques pour mesurer la profondeur
G01C 19/00 - GyroscopesDispositifs sensibles à la rotation utilisant des masses vibrantesDispositifs sensibles à la rotation sans masse en mouvementMesure de la vitesse angulaire en utilisant les effets gyroscopiques
G01P 15/00 - Mesure de l'accélérationMesure de la décélérationMesure des chocs, c.-à-d. d'une variation brusque de l'accélération
A flexible feature and location-based listings system can provide accommodation listings using different feature categories and a location of the searching user. The returned listings can be modified upon providing the listings to a searching user. The returned listings can be modified in response to selection of a first feature category and re-modified in response to a second feature category in an expanded geographic search area.
G06Q 10/02 - Réservations, p. ex. pour billetterie, services ou manifestations
G06F 16/587 - 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
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
36 - Services financiers, assurances et affaires immobilières
37 - Services de construction; extraction minière; installation et réparation
38 - Services de télécommunications
39 - Services de transport, emballage et entreposage; organisation de voyages
41 - Éducation, divertissements, activités sportives et culturelles
42 - Services scientifiques, technologiques et industriels, recherche et conception
43 - Services de restauration (alimentation); hébergement temporaire
45 - Services juridiques; services de sécurité; services personnels pour individus
Produits et services
Computer software, especially for mobile devices. Providing an online business directory; providing a web site featuring the ratings, reviews, recommendations and comments posted by users relating to service providers for commercial purposes; advertising and marketing in the fields of tourism and travel; advertising and promotion services relating to providers of services on online platforms; providing online computer databases and online searchable databases featuring the offers of service providers; providing consumer service information via the Internet; business consulting and management services; office functions. Electronic commerce payment services, especially processing payments in connection with services booked on an online platform. Arranging and facilitating of cleaning services. Providing access to platforms on the Internet; electronic transmission of messages. Travel reservation services; Providing travel and tour information over global computer networks; travel arrangement; arranging of travel tours; reservation of travel tours. Providing electronic newsletters relating to travel, lodging, education, entertainment, sporting and cultural activities; education, entertainment, sporting and cultural activities as well as corresponding reservation services; photography services. Providing temporary use of non-downloadable, web-based, and cloud-based software; software as a service (SaaS) services; platform as a service (PaaS) services; Providing an online non downloadable, web-based and cloud-based software platform. Providing online reservation services for temporary lodging; providing temporary lodging information via the Internet and via newsletters; arranging temporary housing accommodations; temporary accommodation; services for providing food and drink and corresponding reservation services. On-line social networking services; providing information in the field of personal and travel concierge services; concierge services.
68.
OUTPUTTING EMOTES BASED ON AUDIENCE MEMBER EXPRESSIONS IN LARGE-SCALE ELECTRONIC PRESENTATION
A presentation service generates an audience interface for an electronic presentation. The audience interface may simulate an in-person presentation, including features such as a central presenter and seat locations for audience members. The audience members may select emotes which may be displayed in the audience interface. The emotes may indicate the audience members' opinion of the content being presented. The presentation service may enable chats between multiple audience members, grouping of audience members private rooms, and other virtual simulations of functions corresponding to in-person presentations.
A flexible listings search system can receive and return results for flexible listing searches. For example, the system can perform micro-flexible searches (e.g., plus or minus a few days) or super flexible searches (e.g., a time span in one or more months), using listing arrays that can be rapidly accessed to efficiently identify and return results. The search system can further perform flexible destination searches for different categories of accommodations for display in a viewport (e.g., map bounding box). The system can further perform fuzzy searches to identify and return broader results for flexible queries.
There is provided a method that includes receiving, from a client device, a search request for a set of listings, the search request including search parameters defining a search query. The method further includes generating a set of listings based on the search query and the search parameters and extracting price-indicative and non-price-indicative features. The method also includes computing a probability of booking and an estimate of quality, by inputting the price-indicative features and non-price-indicative features to trained machine learning models. The trained machine learning models predict (i) an affordability metric based on the price-indicative features and (ii) a quality metric based on the non-price-indicative features, separately. The affordability metric and the quality metric are representative of the probability of booking, and the quality metric is representative of the estimate of quality. The method further includes ranking the set of listings based on the booking probability and the quality estimate.
Two sets of data, each containing property listings, are obtained from two discrete merchant platforms. Each property listing in a set of data of a first merchant is sequentially paired with each of the property listings in a set of data of a second merchant. For each pair, each image of the property listing of the first merchant is compared to each image of the property listing of the second merchant, and images of statistically sufficient similarity are identified. The similarity of images, and in particular, of similar images likely to be rooms of the property, are considered in a determination of whether the product listings of the first and second merchant are for the same cross-listed product.
G06F 16/29 - Bases de données d’informations géographiques
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
G06Q 10/02 - Réservations, p. ex. pour billetterie, services ou manifestations
G06V 10/75 - Organisation de procédés de l’appariement, p. ex. comparaisons simultanées ou séquentielles des caractéristiques d’images ou de vidéosApproches-approximative-fine, p. ex. approches multi-échellesAppariement de motifs d’image ou de vidéoMesures de proximité dans les espaces de caractéristiques utilisant l’analyse de contexteSélection des dictionnaires
G06Q 30/0201 - Modélisation du marchéAnalyse du marchéCollecte de données du marché
A method for depicting location attributes in a map environment. The method includes receiving a request for parameters about a first type of location. The method includes determining a first set of directional arrows, where each directional arrow is associated with a location and has a first set of properties based on the parameters about the first type of location. The method further includes determining a selection of a first directional arrow, which is associated with a first location, from the first set of directional arrows. Modifications to the first set of directional arrows are made based on the selection of the first directional arrow.
A search system that receives and returns results for split stays is described. The search system receives, from a searching end-user, a listing request specifying a multiple-day length of stay parameter. The search system determines that the multiple-day length of stay parameter of the listing request transgresses a minimum length of stay threshold and, in response, generates a combined listing that includes a first listing of the plurality of listings associated with a first portion of the multiple-day length of stay parameter and a second listing of the plurality of listings associated with a second portion of the multiple-day length of stay parameter. The combined listing is presented with one or more other listings of the plurality of listings that match the listing request in a ranked order.
A search system that receives and returns results for split stays is described. The search system receives, from a searching end-user, a listing request specifying a multiple-day length of stay parameter. The search system determines that the multiple-day length of stay parameter of the listing request transgresses a minimum length of stay threshold and, in response, generates a combined listing that includes a first listing of the plurality of listings associated with a first portion of the multiple-day length of stay parameter and a second listing of the plurality of listings associated with a second portion of the multiple-day length of stay parameter. The combined listing is presented with one or more other listings of the plurality of listings that match the listing request in a ranked order.
Systems and methods are provided to generate an access code specific to a user of an online marketplace to use to enter a first accommodation during a first reservation time frame and a second accommodation during a second reservation time frame and to send the access code specific to the user to a computing device at the first accommodation and a computing device at the second accommodation to use to enter the first accommodation during the first reservation time period and the second accommodation during the second reservation time period. The access code is automatically removed from the computing device at the first accommodation and the computing device at the second accommodation at the end of the first reservation time period and at the end of the second reservation time period, respectively.
G07C 9/38 - Enregistrement de l’entrée ou de la sortie d'une entité isolée ne comportant pas l’utilisation d’un laissez-passer une station centrale gérant l’enregistrement
G06Q 10/02 - Réservations, p. ex. pour billetterie, services ou manifestations
G07C 9/20 - Enregistrement de l’entrée ou de la sortie d'une entité isolée comportant l’utilisation d’un laissez-passer
G07C 9/27 - Enregistrement de l’entrée ou de la sortie d'une entité isolée comportant l’utilisation d’un laissez-passer une station centrale gérant l’enregistrement
H04L 12/28 - Réseaux de données à commutation caractérisés par la configuration des liaisons, p. ex. réseaux locaux [LAN Local Area Networks] ou réseaux étendus [WAN Wide Area Networks]
81.
Cross-listed property matching using image descriptor features
Two sets of data, each containing property listings, are obtained from two discrete merchant platforms. Each property listing in a set of data of a first merchant is sequentially paired with each of the property listings in a set of data of a second merchant. For each pair, each image of the property listing of the first merchant is compared to each image of the property listing of the second merchant, and images of statistically sufficient similarity are identified. The similarity of images, and in particular, of similar images likely to be rooms of the property, are considered in a determination of whether the product listings of the first and second merchant are for the same cross-listed product.
G06F 16/29 - Bases de données d’informations géographiques
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
G06Q 10/02 - Réservations, p. ex. pour billetterie, services ou manifestations
G06Q 30/0201 - Modélisation du marchéAnalyse du marchéCollecte de données du marché
G06V 10/75 - Organisation de procédés de l’appariement, p. ex. comparaisons simultanées ou séquentielles des caractéristiques d’images ou de vidéosApproches-approximative-fine, p. ex. approches multi-échellesAppariement de motifs d’image ou de vidéoMesures de proximité dans les espaces de caractéristiques utilisant l’analyse de contexteSélection des dictionnaires
Systems and methods are provided to analyze at least one sensor of a computing device to determine that the computing device is in a substantially flat position on the first surface, activate a camera comprising a depth sensor, and detect a second surface in a camera view of the camera. The computing device further analyzes pixel measurements from the depth sensor in a predefined area of the detected second surface to determine a minimum measurement of all of the pixel measurements in the predefined area of the detected surface, causes display of the minimum measurement from the first surface to the second surface overlaid on an image of the first and second surface in the camera view on a user interface of the computing device, and captures an image of the display.
G01B 11/22 - Dispositions pour la mesure caractérisées par l'utilisation de techniques optiques pour mesurer la profondeur
G01C 19/00 - GyroscopesDispositifs sensibles à la rotation utilisant des masses vibrantesDispositifs sensibles à la rotation sans masse en mouvementMesure de la vitesse angulaire en utilisant les effets gyroscopiques
G01P 15/00 - Mesure de l'accélérationMesure de la décélérationMesure des chocs, c.-à-d. d'une variation brusque de l'accélération
A presentation service generates an audience interface for an electronic presentation. The audience interface may simulate an in-person presentation, including features such as a central presenter and seat locations for audience members. The audience members may select emotes which may be displayed in the audience interface. The emotes may indicate the audience members' opinion of the content being presented. The presentation service may enable chats between multiple audience members, grouping of audience members private rooms, and other virtual simulations of functions corresponding to in-person presentations.
Highly user-specific data is used to calculate user intent to make a purchase and the value of such a purchase. User activity and information is aggregated, per user, for a set window of time and real-time data on recent site behavior is obtained. Aggregated and/or real-time data is considered by a predictive intent model (calculating the probability that the user will make a purchase) and a predictive value model (calculating the expected revenue such a purchase may generate). Weights, specific to each model, are assigned to predictor features tracked in the aggregated and/or real-time user data. The most highly-weighted features of the intent model relate to users' viewing history, and the most highly-weighted features of the value model relate to price and market. By these means, a user conversion value can be obtained, guiding the application of user acquisition strategies for different home sharing markets.
A user is associated with initial search requests, and results that comprise attribute types indicative of a common relationship with other results. Each result has an attribute parameter for each attribute type. Search interaction data. Search interaction data comprises attribute parameter data and user interaction data for the search results. A machine learning algorithm is trained to analyze the search interaction data to recognize common relationships, and used to detect a common relationship between the respective attribute parameters for one of the attribute types for which the user interest data indicates interest. When a subsequent search request is received from the user, a user interest characteristic is computed for each result, based on similarity between the attribute preference data detected using the machine learning algorithm and the attribute parameter for the attribute type. The search results are presented to the user, sorted according to user interest characteristic.
System receives request from user for decision making options, and provide gameplan document that suggests accessing first and second data source to collect options. System extracts first data records set from content copied by user from first data source, and inserts first data records set in first table in gameplan document. System extracts second data records set from content copied by user from second data source, and inserts second data records set in second table in gameplan document. System inserts combined data records set, based on first data records set joined with second data records set, in combined data table in gameplan document. System enables user to identify candidates, for options, in combined data records set in response to user commands. System determines overall scores corresponding to candidates, based on applying criteria, scored by user, to each candidate. System outputs candidates, ranked based on corresponding scores, as decision making options.
A server obtains content in a first language and receives a first request from a first client device to view the content, wherein the first client device is associated with a second language selected by a user operating the first client device. In response to receiving the first request, the server determines that the first language is different from the second language and determines that a storage of the server does not include a machine-translated version of the content in the second language. In accordance with these determinations, the server obtains a machine-translated version of the content in the second language and stores the machine-translated version of the content in the second language in the storage for subsequent requests to view the content in the second language.
G06F 40/58 - Utilisation de traduction automatisée, p. ex. pour recherches multilingues, pour fournir aux dispositifs clients une traduction effectuée par le serveur ou pour la traduction en temps réel
There is provided a method that includes receiving, from a client device, a search request for a set of listings, the search request including search parameters defining a search query. The method further includes generating a set of listings based on the search query and the search parameters and extracting price-indicative and non-price-indicative features. The method also includes computing a probability of booking and an estimate of quality, by inputting the price-indicative features and non-price-indicative features to trained machine learning models. The trained machine learning models predict (i) an affordability metric based on the price-indicative features and (ii) a quality metric based on the non-price- indicative features, separately. The affordability metric and the quality metric are representative of the probability of booking, and the quality metric is representative of the estimate of quality. The method further includes ranking the set of listings based on the booking probability and the quality estimate.
A server obtains content in a first language and receives a first request from a first client device to view the content, wherein the first client device is associated with a second language selected by a user operating the first client device. In response to receiving the first request, the server determines that the first language is different from the second language and determines that a storage of the server does not include a machine-translated version of the content in the second language. In accordance with these determinations, the server obtains a machine-translated version of the content in the second language and stores the machine-translated version of the content in the second language in the storage for subsequent requests to view the content in the second language.
G06F 40/58 - Utilisation de traduction automatisée, p. ex. pour recherches multilingues, pour fournir aux dispositifs clients une traduction effectuée par le serveur ou pour la traduction en temps réel
Highly user-specific data is used to calculate user intent to make a purchase and the value of such a purchase. User activity and information is aggregated, per user, for a set window of time and real-time data on recent site behavior is obtained. Aggregated and/or real-time data is considered by a predictive intent model (calculating the probability that the user will make a purchase) and a predictive value model (calculating the expected revenue such a purchase may generate). Weights, specific to each model, are assigned to predictor features tracked in the aggregated and/or real-time user data. The most highly-weighted features of the intent model relate to users' viewing history, and the most highly-weighted features of the value model relate to price and market. By these means, a user conversion value can be obtained, guiding the application of user acquisition strategies for different home sharing markets.
A presentation service generates an audience interface for an electronic presentation. The audience interface may simulate an in-person presentation, including features such as a central presenter and seat locations for audience members. The audience members may select emotes which may be displayed in the audience interface. The emotes may indicate the audience members' opinion of the content being presented. The presentation service may enable chats between multiple audience members, grouping of audience members private rooms, and other virtual simulations of functions corresponding to in-person presentations.
Systems and methods are provided for receiving a request for services in a given location from a client device operated by a user and generating a set of features based on information included in the request for services in the given location. The systems and methods further provide for analyzing the set of features using a machine learning model to predict whether only services that can be instantly booked should be provided in response to the request for services in the given location, analyzing a prediction output by the machine learning model to determine that only services that can be instantly booked should be provided in response to the request for services in the given location, and generating a list with only services that can be instantly booked.
