A consent verification checker is an application operating on an operator device that verifies that a consent tag for a consent management platform has been properly installed by a webpage operator and that the consent management platform is operating and is configured correctly. The consent verification checker executes on the operator device and detects issues with the installation of the consent tag and the operation of the CMP based on webpage execution data describing the execution of instructions for displaying the webpage. When using the consent verification checker, a webpage operator can determine whether they have correctly installed a consent tag on their webpage, and that their CMP is operating and configured correctly, by easily loading and displaying their webpage on their own client device, without significant web page technical debugging and diagnostic skills.
A contextual optimization system consistently and reliably determines the context of locations of content and provides an interactive user interface that enables optimization of selection of highly relevant content locations by easily viewing the intersection of information related to actual content, relevance of context, and selections of content locations.
A contextual optimization system consistently and reliably determines the context of locations of content and provides an interactive user interface that enables optimization of selection of highly relevant content locations by easily viewing the intersection of information related to actual content, relevance of context, and selections of content locations.
A consent system enables a consumer to save consent choices so that the publisher can retrieve the consumer consent choices when the consumer visits the publisher site, without requiring the consumer to make additional selections corresponding to consent choices. The consumer can save consent choices as a consent system first party cookie or in an account at the consent system. The consumer can save consent choices when visiting a publisher site or by accessing the consent system. The publisher can retrieve the consumer consent choices from the consent system first party cookie or from the account at the consent system. Multiple publishers can retrieve the consumer consent choices saved in an account with the consent system, enabling “cross-platform consent.”
A videoconferencing system receives audio and/or video signals (“AV”), information, and control signals from meeting participants. The videoconferencing system processes and routes the received AV and information, based on the received control signals, to provide AV and information to meeting participants. The videoconferencing system enables participants to know details about breakout room (e.g., what breakout rooms are available, how many people are attending each breakout room, who is attending each breakout room, the topics of the breakout rooms), hear audio, see video, and receive information corresponding breakout rooms that they have not joined, join a breakout room, leave a breakout room, create breakout rooms, invite other participants to join a breakout room, and make a breakout room private.
H04L 65/1093 - In-session procedures by adding participantsIn-session procedures by removing participants
H04L 65/401 - Support for services or applications wherein the services involve a main real-time session and one or more additional parallel real-time or time sensitive sessions, e.g. white board sharing or spawning of a subconference
H04L 65/403 - Arrangements for multi-party communication, e.g. for conferences
A dynamically regulated advertising delivery control system. A campaign is operated by sending bids to an exchange responsive to receiving bid requests from the exchange, each bid request representing an opportunity to expose a browser to content. Won bid notifications are received from the exchange and exposure notifications are received from exposed browsers. Failed exposures are detected by detecting won bid notification identifiers without corresponding exposure notification identifiers. Responsive to the failed exposures exceeding an upper limit, the campaign is operated in a throttled mode. Responsive to detecting successful exposures in the throttled mode, the campaign is operated in a recovered mode.
An influence system for predicting advertisement impact for audience selection. An advertising probe campaign is operated by sending an advertisement to each entity in a treatment group of entities. A control group of entities which excludes the treatment group entities is selected and no campaign advertising content is sent to the treatment group entities. An influence model is created by comparing features of the treatment group converters to features of the control group converters. An individual frequency cap is selected for each entity that is a candidate for the advertising campaign based on a result of applying the influence model to the features of the candidate entity. The entity may be selected to receive an advertisement based on the individual frequency cap. Some embodiments are integrated with a real time bidding (RTB) exchange and a bid response may be configured based on the results of applying the influence model.
An influence system for predicting advertisement impact for advertising response selection. A treatment group of entities is selected which have received an advertising treatment of a campaign. A control group of entities is selected which excludes the treatment group entities is selected which have not received the advertising treatment of the campaign. An influence model is created for each campaign by comparing features of the treatment group converters to features of the control group converters. A campaign is selected for an opportunity to expose a specified entity to advertising based on the result of applying each respective campaign's influence model to features of the specified entity.
A code manager system provides access to a domain in a container in the code manager system. A user navigates to elements in the domain in the container. The user selects code options from within the code manager system. The code manager system uses the selected code options to generate code for insertion in the domain HTML code. The code manager saves previously defined code and the user updates code options in the code manager system. The code manager system provides pointer codes to insert in the domain HTML code so the user can update stored codes without updating the HTML code.
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
Adaptive control of exposure. A proportional exposure cap is a maximum fraction applicable to a recipient's total viewable attention in a time window. The total viewable attention represents all viewable advertising content which will be provided to the recipient. A notification of availability of an opportunity to expose a specified recipient to advertising content is received during the time window. The specified recipient's consumed viewable attention is detected. The specified recipient's total viewable attention for the time window is predicted. Responsive to the maximum fraction of the specified recipient's predicted total viewable attention for the time window being greater than the consumed viewable attention of the specified recipient, content is sent to the specified recipient and the consumed viewable attention is updated.
A videoconferencing system receives audio and/or video signals (“AV”), information, and control signals from meeting participants. The videoconferencing system processes and routes the received AV and information, based on the received control signals, to provide AV and information to meeting participants. The videoconferencing system enables participants to to know details about breakout room (e.g., what breakout rooms are available, how many people are attending each breakout room, who is attending each breakout room, the topics of the breakout rooms), hear audio, see video, and receive information corresponding breakout rooms that they have not joined, join a breakout room, leave a breakout room, create breakout rooms, invite other participants to join a breakout room, and make a breakout room private.
H04L 65/401 - Support for services or applications wherein the services involve a main real-time session and one or more additional parallel real-time or time sensitive sessions, e.g. white board sharing or spawning of a subconference
H04L 65/1093 - In-session procedures by adding participantsIn-session procedures by removing participants
An adaptive bidding system for networked advertising. A bid request is received from an exchange over a network. Each bid request represents the opportunity to bid on an advertising opportunity. A processing time limit is determined based at least in part on a network latency measurement and an exchange reported timeout. The execution of one or more tasks is initiated by the adaptive bidding system. A response is determined from one or more results which are available before the processing time limit expires. The execution of any tasks that have not completed execution before the processing time limit expires are terminated. The response is provided to the exchange.
Protected audience selection system. Media consumption histories of browsers which have converted are received at a modeling system where targeting of browsers is prohibited. A model is built by determining a frequency of each respective media consumption event among the histories and comparing each determined frequency of a respective media consumption event to a frequency of the respective media consumption event among a population of browsers without the conversion event. The model is sent to a targeting system which excludes conversion events. A description of the conversion event is received at the targeting system. A history of a targetable browser is received at the targeting system. The model is applied to the history of the targetable browser at the targeting system, where conversion events have been excluded from the history. Advertising content is sent to the targetable browser according to a result of applying the model.
An adaptive bidding system for networked advertising. A bid request is received from an exchange over a network. Each bid request represents the opportunity to bid on an advertising opportunity. A processing time limit is determined based at least in part on a network latency measurement and an exchange reported timeout. The execution of one or more tasks is initiated by the adaptive bidding system. A response is determined from one or more results which are available before the processing time limit expires. The execution of any tasks that have not completed execution before the processing time limit expires are terminated. The response is provided to the exchange.
Embodiments of the invention include a system for automated persona feature selection. Soft clusters of entities are received, each entity having a history of features. Each feature has a general prevalence coefficient representing prevalence of entities having the respective feature in their history. A feature list is generated for each cluster, each feature having an in-cluster coefficient representing prevalence of entities in the cluster having the feature in their history. Features having an in-cluster coefficient that is different from that feature's general prevalence coefficient are selected. A variance across the clusters is determined for each selected feature. A discriminating feature list having high variance features is generated for each cluster. Clusters are selected for an entity by comparing the features of the entity's history to features of the discriminating feature lists of the clusters. Content is customized according to the chosen clusters and sent to the entity.
A control system determines whether a browser is retrieving supplemental content over a slow or faulty network using a tracking indicator. Based on determining that browser is retrieving supplemental content over a slow or faulty network, the control system modifies responses to opportunities to provide supplemental content to the browser. The control system may modify responses by declining to bid, responding with a lower bid amount, or responding with alternate supplemental content. Based on determining that browser is no longer retrieving supplemental content over a slow or faulty network, the control system modifies responses to opportunities to provide supplemental content to the browser by responding with a higher bid amount or responding with the original supplemental content. Thus, the control system maximizes the use of control system and campaign manager resources by responding to opportunities according to the likelihood that they will result in an impression or a conversion.
Method and system for assessing the suitability of an entity using a proxy. A description of a behavior associated with a desirable audience is received. A proxy behavior estimated to be characteristic of the desirable audience is selected. The proxy behavior comprises the performance of proxy events related to the consumption of media received by an entity over a network, which can be found in an entity's consumption history. An entity can be assessed for inclusion in a proxy audience, by examining the entity's consumption history for proxy behaviors. A behavioral model is built using a training set comprising the proxy audience. By applying the behavioral model to the consumption history of a specified entity, the specified entity's suitability for selection can be determined. Advantageously, in an embodiment, the invention enables the use of behavioral modeling techniques even when the complete behavior of the desirable audience is not available.
A tag manager system provides access to a domain in a container in the tag manager system. A tag user navigates to an element in the domain (such as site pages, text elements, graphic elements, or video elements) and selects the element to validate its tag code from within the container. Based on results of the validation, the tag manager system updates the tag code corresponding to the element.
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
Protected audience selection system. Media consumption histories of browsers which have converted are received at a modeling system where targeting of browsers is prohibity. A model is built by determining a frequency of each respective media consumption event among the histories and comparing each determined frequency of a respective media consumption event to a frequency of the respective media consumption event among a population of browsers without the conversion event. The model is sent to a targeting system which excludes conversion events. A description of the conversion event is received at the targeting system. A history of a targetable browser is received at the targeting system. The model is applied to the history of the targetable browser at the targeting system, where conversion events have been excluded from the history. Advertising content is sent to the targetable browser according to a result of applying the model.
Privacy centric feature analysis. A secure set of multiple mapped features is selected and provided to a mobile device. Each mapped feature maps a sharable feature to a matching criterion for an item of protected information and no combination of mapped features for a secure set are unique to an individual item of protected information. Privacy compliance instructions enable the mobile device to select a mapped feature from a received set of mapped features by identifying an item of protected information available to the mobile device which corresponds to a matching criterion found in the received set of mapped features. The sharable feature of the selected mapped feature is provided. Advantageously, the analysis system protects the privacy of the mobile device user because it does not require the mobile device to relay protected information for the selection of customized content or relevant advertisements.
H04W 12/02 - Protecting privacy or anonymity, e.g. protecting personally identifiable information [PII]
H04W 4/029 - Location-based management or tracking services
H04W 4/02 - Services making use of location information
H04M 1/72463 - User interfaces specially adapted for cordless or mobile telephones with means for adapting the functionality of the device according to specific conditions to restrict the functionality of the device
H04W 4/021 - Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
A control system determines whether a browser is retrieving supplemental content over a slow or faulty network using a tracking indicator. Based on determining that browser is retrieving supplemental content over a slow or faulty network, the control system modifies responses to opportunities to provide supplemental content to the browser. The control system may modify responses by declining to bid, responding with a lower bid amount, or responding with alternate supplemental content. Based on determining that browser is no longer retrieving supplemental content over a slow or faulty network, the control system modifies responses to opportunities to provide supplemental content to the browser by responding with a higher bid amount or responding with the original supplemental content. Thus, the control system maximizes the use of control system and campaign manager resources by responding to opportunities according to the likelihood that they will result in an impression or a conversion.
Adaptive control of exposure. A proportional exposure cap is a maximum fraction applicable to a recipient's total viewable attention in a time window. The total viewable attention represents all viewable advertising content which will be provided to the recipient. A notification of availability of an opportunity to expose a specified recipient to advertising content is received during the time window. The specified recipient's consumed viewable attention is detected. The specified recipient's total viewable attention for the time window is predicted. Responsive to the maximum fraction of the specified recipient's predicted total viewable attention for the time window being greater than the consumed viewable attention of the specified recipient, content is sent to the specified recipient and the consumed viewable attention is updated.
Embodiments of the invention generate metrics quantifying the mobility of a mobile device without persisting information related to the device's specific location at any given time. Specifically, at multiple intervals, a value of a mobility metric is computed based on the distance between the current location of the mobile device and a previously identified origin location of the mobile device.
H04W 4/02 - Services making use of location information
H04W 4/029 - Location-based management or tracking services
H04W 64/00 - Locating users or terminals for network management purposes, e.g. mobility management
G01S 5/00 - Position-fixing by co-ordinating two or more direction or position-line determinationsPosition-fixing by co-ordinating two or more distance determinations
G01S 5/02 - Position-fixing by co-ordinating two or more direction or position-line determinationsPosition-fixing by co-ordinating two or more distance determinations using radio waves
H04L 67/52 - Network services specially adapted for the location of the user terminal
H04W 8/02 - Processing of mobility data, e.g. registration information at HLR [Home Location Register] or VLR [Visitor Location Register]Transfer of mobility data, e.g. between HLR, VLR or external networks
24.
Conversion timing prediction for networked advertising
A conversion timing model is model is configured to predict a likelihood of conversion based on an entity's elapsed time since a qualified entry event and based on a funnel state. The conversion timing model is constructed based on a distribution of the conversion timespans of converters. A notification of an opportunity to expose a candidate entity to networked content is received. A time-based likelihood of conversion for the candidate entity is determined by applying the conversion timing model to the elapsed time. A response to the notification based on the likelihood of conversion for the candidate entity is prepared based on the time-based likelihood of conversion and based on the funnel state. Timely responses may include the selection of customized content or bid values.
A data operations system receives compressed data and a search term. The data operations system completes a modified decoding of the compressed data, resulting in distinguishable data terms that are smaller than the corresponding data terms, and loads modified decoded terms into a data register. The data operations system generates a truncated search term and loads instances of the truncated search term into a query register. The data operations system performs a parallel data operation, such as a query operation, by comparing each of the modified decoded terms to an instance of the truncated search term. The data operations system returns the results of the operation.
42 - Scientific, technological and industrial services, research and design
Goods & Services
Providing online non-downloadable software for tracking, managing, and optimizing advertising and promotional campaigns, and calculating return on investment in connection with the same; providing online non-downloadable software for tracking website traffic, e-commerce activity, customer loyalty, and sales conversion rates; providing online non-downloadable software for managing, collecting, monitoring and analyzing website traffic, user preferences and links in real time; providing online non-downloadable software for tracking, analyzing, monitoring, measuring and reporting on brand lift, namely, consumer behavior in response to online advertising; providing online non-downloadable software for tracking, analyzing, monitoring, measuring and reporting on brand lift, namely, consumer behavior in response to online advertising; providing online non-downloadable software for real-time tracking, analyzing, monitoring, measuring and reporting on brand lift, namely, consumer behavior in response to online advertising; software as a service (SAAS) services featuring software for digital media measurement, website audience analysis and advertising optimization; software as a services (SAAS) services, namely, hosting software for use by others for managing, monitoring, tracking, and optimizing the performance and effectiveness of online and offline marketing campaigns; software as a service (SAAS) services featuring software for personalization, content targeting, behavioral targeting, and segmentation of advertisements; software as a service (SAAS) services featuring software for tracking, analyzing, monitoring, measuring and reporting on brand lift, namely, consumer behavior in response to online advertising; software as a service (SAAS) services featuring software for real-time tracking, analyzing, monitoring, measuring and reporting on brand lift, namely, consumer behavior in response to online advertising
27.
Privacy-safe frequency distribution of geo-features for mobile devices
A device's location and an identifier corresponding to the device are received. The device's location is privatized by mapping it to landmarks proximate to the device's location, storing the proximate landmarks in association with the device's identifier, and discarding the received location data. The proximate landmarks are featurized to generate a model which is used to determine a value of the advertising opportunity corresponding to a target identifier.
Adaptive control of exposure. A proportional exposure cap is a maximum fraction applicable to a recipient's total viewable attention in a time window. The total viewable attention represents all viewable advertising content which will be provided to the recipient. A notification of availability of an opportunity to expose a specified recipient to advertising content is received during the time window. The specified recipient's consumed viewable attention is detected. The specified recipient's total viewable attention for the time window is predicted. Responsive to the maximum fraction of the specified recipient's predicted total viewable attention for the time window being greater than the consumed viewable attention of the specified recipient, the advertising campaign's advertising content is sent to the specified recipient and the consumed viewable attention is updated.
A data operations system receives compressed data and a search term. The data operations system completes a modified decoding of the compressed data, resulting in distinguishable data terms that are smaller than the corresponding data terms, and loads modified decoded terms into a data register. The data operations system generates a truncated search term and loads instances of the truncated search term into a query register. The data operations system performs a parallel data operation, such as query operation, by comparing each of the modified decoded terms to an instance of the truncated search term. The data operations system returns the results of the operation.
Online advertising campaigns are operated responsive to keyword trends. The keywords used by a group of browsers is analyzed periodically over time. A list of the most frequently used keywords is separated into those that have previously appeared on the list, referred to herein as the stable keywords, and those that are newly emerging, referred to herein as the trending keywords. The advertiser selects at least one advertising creative that the advertiser associates with the stable keywords, referred to herein as the stable creative, and at least one advertising creative that the advertiser associates with the trending keywords, referred to herein as the trendy creative. The advertising system then operates the online advertising campaign to deliver the respective stable and trendy creatives in proportion to the frequency of use of the trending versus the stable keywords.
A mobile device's location and an identifier corresponding to the mobile device is received. The mobile device's location is privatized by mapping it to landmarks proximate to the mobile device's location, storing the proximate landmarks in association with the mobile device's identifier, and discarding the received location data. The proximate landmarks are featurized to generate a model which is used to determine a value of the advertising opportunity corresponding to a target identifier.
A dynamically regulated advertising delivery control system. A campaign is operated by sending bids to an exchange responsive to receiving bid requests from the exchange, each bid request representing an opportunity to expose a browser to content. Won bid notifications are received from the exchange and exposure notifications are received from exposed browsers. Failed exposures are detected by detecting won bid notification identifiers without corresponding exposure notification identifiers. Responsive to the failed exposures exceeding an upper limit, the campaign is operated in a throttled mode by sending bids to the exchange in response to a fraction of the suitable bid requests received from the exchange and ignoring some suitable bid requests. Responsive to detecting successful exposures in the throttled mode, the operation of the campaign is dynamically regulated by increasing the fraction.
Adaptive Sampling. Data comprising pairings of data value with lists of data keys are received. The range of possible values of the data keys is partitioned into unbalanced buckets, with at least two of the unbalanced buckets representing different fractions of the range. Each unbalanced bucket is assigned to a respective processing unit selected from a plurality of processing units. The pairings are processed by the processing units, with each processing unit generating an intermediate result. The intermediate results are combined to generate a comprehensive result. A sampling error is determined by scaling an unbalanced bucket's intermediate result according to its corresponding fraction and comparing the scaled intermediate result to the comprehensive result. An unbalanced bucket having a sampling error less than a sampling error threshold is selected. The selected unbalanced bucket's corresponding fraction is selected as a sampling rate for a second data processing job.
A tag manager system provides access to a domain in a container in the tag manager system. A tag user navigates to elements in the domain (such as site pages, text elements, graphic elements, or video elements) and selects elements for tagging from within the container. The user selects tag options from within the tag manager system. The tag manager system uses the selected tag options to generate the corresponding tag codes for insertion in the domain HTML code. The tag manager saves previously defined tag codes and the tag user updates stored tag options in the tag manager system. The tag manager system provides pointer codes to insert in the HTML code so the user can update stored tag codes without updating the HTML code. The tag manager further highlights elements of the domain in the container for suggested tagging, and automatically selects option based on the element type.
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
35.
Selective regulation of information transmission from mobile applications to third-party privacy compliant target systems
Selective regulation of information transmission from mobile applications to an external system. A privacy policy is configured for and mapped to each of a multiplicity of mobile application concerns, with each privacy policy comprising rules regulating the transmission of information to an external system. Instrumentation instructions can be integrated with a mobile application or mobile operating system. The instrumentation instructions direct the mobile device to submit a privacy policy request comprising an identifier from the mobile device to a third-party privacy compliance system and enable sending information from the mobile device to the external system, subject to the privacy policy. The privacy policy request is received at the third-party privacy compliance system which selects the privacy policy based on an identifier and sends the privacy policy to the mobile device for implementation.
Online advertising campaigns are operated responsive to keyword trends. The keywords used by a group of browsers is analyzed periodically over time. A list of the most frequently used keywords is separated into those that have previously appeared on the list, referred to herein as the stable keywords, and those that are newly emerging, referred to herein as the trending keywords. The advertiser selects at least one advertising creative that the advertiser associates with the stable keywords, referred to herein as the stable creative, and at least one advertising creative that the advertiser associates with the trending keywords, referred to herein as the trendy creative. The advertising system then operates the online advertising campaign to deliver the respective stable and trendy creatives in proportion to the frequency of use of the trending versus the stable keywords.
A distributed system is adapted to manage the performance of distributed processes. In one aspect, multiple stripes associated with a data item are stored in a distributed storage. The stored stripes may include one or more stripes of redundancy information for the data item. The stored stripes may include one or more copies of stripes for the data item. A distributed process including at least one task is performed. During performance of the distributed process, a determination is made as to whether to perform an accelerated data retrieval operation. Responsive to a determination to perform an accelerated data retrieval operation, at more than the minimal number stripes information required to reconstruct the data item is requested from the distributed storage. After a sufficient subset of stripes associated with the data item is received, the data item is reconstructed using the subset.
G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
G06F 11/10 - Adding special bits or symbols to the coded information, e.g. parity check, casting out nines or elevens
G06F 3/06 - Digital input from, or digital output to, record carriers
H04L 29/08 - Transmission control procedure, e.g. data link level control procedure
A dynamically regulated advertising delivery control system. A campaign is operated by sending bids to an exchange responsive to receiving bid requests from the exchange, each bid request representing an opportunity to expose a browser to content. Won bid notifications are received from the exchange and exposure notifications are received from exposed browsers. Failed exposures are detected by detecting won bid notification identifiers without corresponding exposure notification identifiers. Responsive to the failed exposures exceeding an upper limit, the campaign is operated in a throttled mode by sending bids to the exchange in response to a fraction of the suitable bid requests received from the exchange and ignoring some suitable bid requests. Responsive to detecting successful exposures in the throttled mode, the operation of the campaign is dynamically regulated by increasing the fraction.
42 - Scientific, technological and industrial services, research and design
Goods & Services
Software-as-a-service (SaaS) services; Software-as-a-service (SaaS) services featuring software using artificial intelligence and machine learning technology; Software-as-a-service (SaaS) services featuring software using artificial intelligence and machine learning technology for receiving, storing, processing, and analyzing online advertising data; Software-as-a-service (SaaS) services featuring software using artificial intelligence and machine learning technology for execution of online advertising campaigns; Software-as-a-service (SaaS) services featuring software using artificial intelligence and machine learning technology for analyzing results of online advertising campaigns; Software-as-a-service (SaaS) services featuring software for website audience analysis and advertising optimization in the field of digital media measurement; Software-as-a-service (SaaS) service featuring software that tracks, and optimizes the performance and effectiveness of online and offline marketing campaigns; Software as a service (SaaS) services, featuring software for personalization, content targeting, behavioral targeting, and segmentation; all of the aforesaid excluding software as a service (SaaS) services for the measuring, testing, calibrating and validating of electronic control apparatus for motor vehicles; all of the aforesaid excluding software as a service (SaaS) services for conducting end user self-assessment of personal health conditions and symptoms, generating health reports, accessing referrals to healthcare providers, and for providing clinical healthcare data analytics.
A tag manager system provides access to a domain in a container in the tag manager system. A tag user navigates to elements in the domain (such as site pages, text elements, graphic elements, or video elements) and selects elements for tagging from within the container. The user selects tag options from within the tag manager system. The tag manager system uses the selected tag options to generate the corresponding tag codes for insertion in the domain HTML code. The tag manager saves previously defined tag codes and the tag user updates stored tag options in the tag manager system. The tag manager system provides pointer codes to insert in the HTML code so the user can update stored tag codes without updating the HTML code. The tag manager further highlights elements of the domain in the container for suggested tagging, and automatically selects option based on the element type.
G06F 40/117 - TaggingMarking up Designating a blockSetting of attributes
G06F 16/958 - Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
An influence system for predicting advertisement impact for audience selection. An advertising probe campaign is operated by sending an advertisement to each entity in a treatment group of entities. A control group of entities which excludes the treatment group entities is selected and no campaign advertising content is sent to the treatment group entities. An influence model is created by comparing features of the treatment group converters to features of the control group converters. An individual frequency cap is selected for each entity that is a candidate for the advertising campaign based on a result of applying the influence model to the features of the candidate entity. The entity may be selected to receive an advertisement based on the individual frequency cap. Some embodiments are integrated with a real time bidding (RTB) exchange and a bid response may be configured based on the results of applying the influence model.
Automatic performance triggered campaign adjustment. A hierarchical feature tree is generated. Each child node's feature is more specific than its respective parent node's feature. The discovery system creates a behavioral model comprising features of the feature tree which is used in the operation of an advertising campaign. A degraded model feature is detected at the discovery system by comparing a performance metric of a model feature from two different time windows. The discovery system matches a node of the feature tree with the degraded feature and selects a prospective model feature from an ancestor node of the matching feature's node. An estimated performance metric for the prospective model feature is determined and the results are used to decide if the prospective model feature should be incorporated into an updated model or not. The model can be updated with a new model feature selected from one or more prospective model features.
Embodiments of the invention generate metrics quantifying the mobility of a mobile device without persisting information related to the device's specific location at any given time. Specifically, at multiple intervals, a value of a mobility metric is computed based on the distance between the current location of the mobile device and a previously identified origin location of the mobile device. The values of the mobility metric computed over a period of time quantify the overall mobility of the mobile device. The mobility metric does not provide any information regarding the specific location of the mobile device at any given time.
H04W 4/02 - Services making use of location information
H04W 4/029 - Location-based management or tracking services
H04W 64/00 - Locating users or terminals for network management purposes, e.g. mobility management
G01S 5/00 - Position-fixing by co-ordinating two or more direction or position-line determinationsPosition-fixing by co-ordinating two or more distance determinations
G01S 5/02 - Position-fixing by co-ordinating two or more direction or position-line determinationsPosition-fixing by co-ordinating two or more distance determinations using radio waves
H04L 29/08 - Transmission control procedure, e.g. data link level control procedure
H04W 8/02 - Processing of mobility data, e.g. registration information at HLR [Home Location Register] or VLR [Visitor Location Register]Transfer of mobility data, e.g. between HLR, VLR or external networks
44.
Managing a distributed system processing a publisher's streaming data
A distributed system processing a publisher's streaming data. The distributed system comprises multiple workers and publisher data stores, each publisher data store dedicated to a worker and a publisher. A sampling ratio (the fraction of data items for storage in the publisher's data store) is selected by a publisher data store's worker based on historical information. At least two workers select different sampling ratios. Data items representing an interaction between an entity and the publisher are received. Each data item is assigned to a worker for processing. A hash function is applied to the data item's identifier, resulting in a key value falling within the hash function's range. The scope of the publisher's data store is equal to the hash function's range multiplied by the sampling ratio of the publisher's data store. A data item with a key value within the scope of the publisher's data store is stored therein.
G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
H04L 29/06 - Communication control; Communication processing characterised by a protocol
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
A hierarchical feature tree is generated. Each child node's feature is more specific than its respective parent node's feature. A behavioral model comprising features of the feature tree is created and used in the operation of an advertising campaign. A degraded model feature is detected at the discovery system by comparing a performance metric of a model feature from two different time windows. The discovery system matches a node of the feature tree with the degraded feature and selects a prospective model feature from a family node. An estimated performance metric for the prospective model feature is determined and the results are used to decide if the model should be updated to include the prospective model feature. The campaign can be operated with the automatically updated model.
42 - Scientific, technological and industrial services, research and design
Goods & Services
Software-as-a-service (SaaS) services featuring software using artificial intelligence and machine learning technology for receiving, storing, processing, and analyzing online advertising data; Software-as-a-service (SaaS) services featuring software using artificial intelligence and machine learning technology for execution of online advertising campaigns; Software-as-a-service (SaaS) services featuring software using artificial intelligence and machine learning technology for analyzing results of online advertising campaigns; Software-as-a-service (SaaS) services featuring software for website audience analysis and advertising optimization in the field of digital media measurement; Software-as-a-service (SaaS) service featuring software that tracks, and optimizes the performance and effectiveness of online and offline marketing campaigns; Software as a service (SaaS) services, featuring software for personalization, content targeting, behavioral targeting, and segmentation of advertising and marketing campaigns
47.
Preserving privacy related to networked media consumption activities
Preserving privacy related to networked media consumption activity. Privacy zones are defined and associated with privacy standards. Privacy standards include frequency criteria governing the storage of datasets including information associated with networked media consumption activity collected from the privacy zone. Transaction requests are received over a network from a client device at a location by a networked privacy system. The privacy zone associated with the client device is identified. A dataset can be created including information associating the networked media consumption activity. The dataset is processed to comply with the privacy standards. The processed dataset can be stored in a database on a physical storage device at a storage location coupled to the networked privacy system.
A tag manager system provides access to a domain in a container in the tag manager system. A tag user navigates to elements in the domain (such as site pages, text elements, graphic elements, or video elements) and selects elements for tagging from within the container. The user selects tag options from within the tag manager system. The tag manager system uses the selected tag options to generate the corresponding tag codes for insertion in the domain HTML code. The tag manager saves previously defined tag codes and the tag user updates stored tag options in the tag manager system. The tag manager system provides pointer codes to insert in the HTML code so the user can update stored tag codes without updating the HTML code. The tag manager further highlights elements of the domain in the container for suggested tagging, and automatically selects option based on the element type.
Embodiments of the invention build models to predict the likelihood of entities that operate in a given identifier space also operating in a disjoined identifier space based on a source panel of entities that operate in one or both of the identifier spaces. In operation, a model building engine builds a model based on features associated with the source panel and features associated with standard populations in the given identifier space. The model is used to determine whether the target entity is more similar to those entities in the source panel that operate only in the given identifier space or those entities in the source panel that operate in both identifier spaces.
Privacy centric feature analysis. A secure set of multiple mapped features is selected and provided to a mobile device. Each mapped feature maps a sharable feature to a matching criterion for an item of protected information and no combination of mapped features for a secure set are unique to an individual item of protected information. Privacy compliance instructions enable the mobile device to select a mapped feature from a received set of mapped features by identifying an item of protected information available to the mobile device which corresponds to a matching criterion found in the received set of mapped features. The sharable feature of the selected mapped feature is identified and sent to a privacy compliant destination. Advantageously, the analysis system protects the privacy of the mobile device user because it does not require the mobile device to relay protected information for the selection of customized content or relevant advertisements.
Encouraging broader engagement with a target publisher's content by balancing on-site topic engagement. Responsive to receiving notification of a recipient's request of an item of content from the target publisher, the on-site and off-site content consumption history of the recipient is analyzed. For each of a plurality of topics, historic engagement with on-site and off-site content is measured. Deficient topics having better off-site engagement than on-site engagement are detected. Content comprising links to items of content available from the target publisher which are characterized by deficient topics is selected and sent to the recipient. In an embodiment, the supplemental content comprises a plurality of links to other web pages on the target publisher's website which are sent to the recipient browser before the requested item of content finishes loading.
A distributed system is adapted to manage the performance of distributed processes. In one aspect, multiple stripes associated with a data item are stored in a distributed storage. The stored stripes include one or more stripes of redundancy information for the data item. A distributed process including at least one task is performed. During performance of the distributed process, a determination is made as to whether to perform an accelerated data retrieval operation. Responsive to a determination to perform an accelerated data retrieval operation, at least one of the one or more stripes of redundancy information for the data item is requested from the distributed storage. Other stripes associated with the data item may also be requested from the distributed storage. After a sufficient subset of stripes associated with the data item is received, the data item is reconstructed using the subset.
G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
G06F 11/10 - Adding special bits or symbols to the coded information, e.g. parity check, casting out nines or elevens
G06F 3/06 - Digital input from, or digital output to, record carriers
An adaptive bidder for networked advertising. A bid request is received from an exchange over a network. Each bid request represents the opportunity to bid on an advertising opportunity. A processing time limit is determined based at least in part on a network latency measurement, an exchange reported timeout and a bid response buffer. The network latency measurement may be required to meet a freshness standard. The bid response buffer represents the time allotted for the adaptive bidding system to generate a response based on one or more partial results. The exchange reported timeout value can be included in the bid request, and can vary from bid request to bid request. The execution of one or more tasks is initiated by the adaptive bidding system, and each task can make a partial result available. In some cases, a partial result is a cumulative result. A response is determined from one or more partial results which are available before the processing time limit expires. The response is provided to the exchange.
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & Services
Downloadable software; downloadable software for selecting, saving, and managing consent preferences regarding website visitor data and mobile application user data; downloadable software for collecting, saving, and managing consent preferences and website visitor data and mobile application user data; downloadable software for selecting, saving, and managing configuration settings for the collection and management of website visitor data and mobile application user data; downloadable software for accessing website visitors and mobile application users' consent preferences regarding website visitor data and mobile application user data; downloadable software for enabling compliance with regulations regarding website visitor data and mobile application user data and website visitor data and mobile application users' consent preferences regarding website visitor data and mobile application user data; downloadable software for enabling website visitors and mobile application users to provide consent regarding website visitor data and mobile application user data in order to sign on to websites and mobile applications; downloadable software to enable website visitors and mobile application to provide consent regarding website visitor data and mobile application user data in order to access website and mobile application content. Software-as-a-service (SaaS) services; Software-as-a-service (SaaS) services featuring software for selecting, saving, and managing consent preferences regarding website visitor data and mobile application user data; Software-as-a-service (SaaS) services featuring software for collecting, saving, and managing consent preferences and website visitor data and mobile application user data; Software-as-a-service (SaaS) services featuring software for selecting, saving, and managing configuration settings for the collection and management of website visitor data and mobile application user data; Software-as-a-service (SaaS) services featuring software for accessing website visitors and mobile application users' consent preferences regarding website visitor data and mobile application user data; Software-as-a-service (SaaS) services featuring software for enabling compliance with regulations regarding website visitor data and mobile application user data and website visitor data and mobile application users' consent preferences regarding website visitor data and mobile application user data; Software-as-a-service (SaaS) services featuring software for enabling website visitors and mobile application users to provide consent regarding website visitor data and mobile application user data in order to sign on to websites and mobile applications; Software-as-a-service (SaaS) services featuring software to enable website visitors and mobile application to provide consent regarding website visitor data and mobile application user data in order to access website and mobile application content; providing online non-downloadable software; providing online non-downloadable software for selecting, saving, and managing consent preferences regarding website visitor data and mobile application user data; providing online non-downloadable software for collecting, saving, and managing consent preferences and website visitor data and mobile application user data; providing online non-downloadable software for selecting, saving, and managing configuration settings for the collection and management of website visitor data and mobile application user data; providing online non-downloadable software for accessing website visitors and mobile application users' consent preferences regarding website visitor data and mobile application user data; providing online non-downloadable software for enabling compliance with regulations regarding website visitor data and mobile application user data and website visitor data and mobile application users' consent preferences regarding website visitor data and mobile application user data; providing online non-downloadable software for enabling website visitors and mobile application users to provide consent regarding website visitor data and mobile application user data in order to sign on to websites and mobile applications; providing online non-downloadable software to enable website visitors and mobile application to provide consent regarding website visitor data and mobile application user data in order to access website and mobile application content.
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & Services
Downloadable software; downloadable software for selecting, saving, and managing consent preferences regarding website visitor data and mobile application user data; downloadable software for collecting, saving, and managing consent preferences and website visitor data and mobile application user data; downloadable software for selecting, saving, and managing configuration settings for the collection and management of website visitor data and mobile application user data; downloadable software for accessing website visitors and mobile application users' consent preferences regarding website visitor data and mobile application user data; downloadable software for enabling compliance with regulations regarding website visitor data and mobile application user data and website visitor data and mobile application users' consent preferences regarding website visitor data and mobile application user data; downloadable software for enabling website visitors and mobile application users to provide consent regarding website visitor data and mobile application user data in order to sign on to websites and mobile applications; downloadable software to enable website visitors and mobile application to provide consent regarding website visitor data and mobile application user data in order to access website and mobile application content. Software-as-a-service (SaaS) services; Software-as-a-service (SaaS) services featuring software for selecting, saving, and managing consent preferences regarding website visitor data and mobile application user data; Software-as-a-service (SaaS) services featuring software for collecting, saving, and managing consent preferences and website visitor data and mobile application user data; Software-as-a-service (SaaS) services featuring software for selecting, saving, and managing configuration settings for the collection and management of website visitor data and mobile application user data; Software-as-a-service (SaaS) services featuring software for accessing website visitors and mobile application users' consent preferences regarding website visitor data and mobile application user data; Software-as-a-service (SaaS) services featuring software for enabling compliance with regulations regarding website visitor data and mobile application user data and website visitor data and mobile application users' consent preferences regarding website visitor data and mobile application user data; Software-as-a-service (SaaS) services featuring software for enabling website visitors and mobile application users to provide consent regarding website visitor data and mobile application user data in order to sign on to websites and mobile applications; Software-as-a-service (SaaS) services featuring software to enable website visitors and mobile application to provide consent regarding website visitor data and mobile application user data in order to access website and mobile application content; providing online non-downloadable software; providing online non-downloadable software for selecting, saving, and managing consent preferences regarding website visitor data and mobile application user data; providing online non-downloadable software for collecting, saving, and managing consent preferences and website visitor data and mobile application user data; providing online non-downloadable software for selecting, saving, and managing configuration settings for the collection and management of website visitor data and mobile application user data; providing online non-downloadable software for accessing website visitors and mobile application users' consent preferences regarding website visitor data and mobile application user data; providing online non-downloadable software for enabling compliance with regulations regarding website visitor data and mobile application user data and website visitor data and mobile application users' consent preferences regarding website visitor data and mobile application user data; providing online non-downloadable software for enabling website visitors and mobile application users to provide consent regarding website visitor data and mobile application user data in order to sign on to websites and mobile applications; providing online non-downloadable software to enable website visitors and mobile application to provide consent regarding website visitor data and mobile application user data in order to access website and mobile application content.
56.
Predicting advertisement impact for campaign selection
An influence system for predicting advertisement impact for campaign selection. For each campaign, an advertising probe campaign is operated by sending an advertisement to each entity in a treatment group of entities. A control group of entities which excludes the treatment group entities is selected and no campaign advertising content is sent to the treatment group entities. An influence model is created for each campaign by comparing features of the respective advertising probe campaign's treatment group converters to features of the control group converters. A campaign is selected for an opportunity to expose a specified entity to advertising based on the result of applying each respective campaign's influence model to features of the specified entity. Advantageously, a campaign operator can make good use of a rare, high quality advertising opportunity by allotting it to an advertising campaign based on a likelihood of influencing the specified entity.
Adaptive control of exposure. A proportional exposure cap is a maximum fraction applicable to a recipient's total viewable attention in a time window. The total viewable attention represents viewable area and exposure duration of all viewable advertising content which will be provided to the recipient. A notification of availability of an opportunity to expose a specified recipient to advertising content is received during the time window. The specified recipient's consumed viewable attention (representing viewable area and exposure duration of the advertising campaign's advertising content) is detected. The specified recipient's total viewable attention for the time window is predicted. Responsive to the maximum fraction of the specified recipient's predicted total viewable attention for the time window being greater than the consumed viewable attention of the specified recipient, the advertising campaign's advertising content is sent to the specified recipient and the consumed viewable attention is updated.
Accesses to a number of data blocks stored in a distributed storage are observed. Following observation of the accesses, the stored data blocks are redistributed. In one aspect, redistribution of the data blocks includes determining the access patterns for one or more of the data blocks based on the observed accesses, and determining the storage sizes for the one or more data blocks. Thereafter, based on the determined access patterns and determined storage sizes, the one or more data blocks are sorted. Subsequently, the one or more data blocks are redistributed or rebalanced across a number of storage devices of the distributed storage based on the sorting. In one aspect, the one or more data blocks are redistributed according to either a uniform distribution scheme or a proportional distribution scheme.
Embodiments of the invention include a system for automated persona feature selection. Soft clusters of entities are received, each entity having a history of features. Each feature has a general prevalence coefficient representing prevalence of entities having the respective feature in their history. A feature list is generated for each cluster, each feature having an in-cluster coefficient representing prevalence of entities in the cluster having the feature in their history. Features having an in-cluster coefficient that is different from that feature's general prevalence coefficient are selected. A variance across the clusters is determined for each selected feature. A discriminating feature list having high variance features is generated for each cluster. Clusters are selected for an entity by comparing the features of the entity's history to features of the discriminating feature lists of the clusters. Content is customized according to the chosen clusters and sent to the entity.
Embodiments are directed to generating and managing an advertising campaign based on a third-party sales listing. In particular, an identifier associated with a sales listing posted over a third-party service from a user of the third-party service is received. Sales listing data for the sales listing is retrieved from the third-party service using the identifier associated with the sales listing. Thereafter, an advertising campaign is automatically generated based at least in part on the retrieved sales listing data. In one aspect, generation of the advertising campaign includes generating an advertising creative using the retrieved sales listing data. Subsequently, bidding on an advertising opportunity in an auction is performed according to the generated advertising campaign. Responsive to winning the auction, an advertisement based on the advertising creative is provided to a content provider associated with the advertising opportunity.
42 - Scientific, technological and industrial services, research and design
Goods & Services
Advertising services; advertising services, namely, placement, and dissemination of online advertising; advertising campaign management services in the nature of tracking, analyzing, and reporting on consumer data, demographics, behavioral information, visits to websites, consumption of media, and responses to advertisements; mediation of advertising; business marketing, promotions, and advertising consulting services; conducting market research and consumer research. Providing online non-downloadable software; Software-as-a-service (SaaS) services; providing online non-downloadable software for tracking, managing, and optimizing advertising and promotional campaigns, and calculating return on investment in connection with the same; providing online non-downloadable software for tracking website traffic, e-commerce activity, customer loyalty, and sales conversion rates; Software-as-a-service (SaaS) services in the field of digital media measurement, website audience analysis and advertising optimization, hosting software that manages, monitors, tracks, and optimizes the performance and effectiveness of online and offline marketing campaigns; Software as a service (SAAS) services, featuring software for personalization, content targeting, behavioral targeting, and segmentation.
42 - Scientific, technological and industrial services, research and design
Goods & Services
Advertising services; advertising services, namely, placement, and dissemination of online advertising; advertising campaign management services in the nature of tracking, analyzing, and reporting on consumer data, demographics, behavioral information, visits to websites, consumption of media, and responses to advertisements; mediation of advertising; business marketing, promotions, and advertising consulting services; conducting market research and consumer research. Providing online non-downloadable software; Software-as-a-service (SaaS) services; providing online non-downloadable software for tracking, managing, and optimizing advertising and promotional campaigns, and calculating return on investment in connection with the same; providing online non-downloadable software for tracking website traffic, e-commerce activity, customer loyalty, and sales conversion rates; Software-as-a-service (SaaS) services in the field of digital media measurement, website audience analysis and advertising optimization, hosting software that manages, monitors, tracks, and optimizes the performance and effectiveness of online and offline marketing campaigns; Software as a service (SAAS) services, featuring software for personalization, content targeting, behavioral targeting, and segmentation.
42 - Scientific, technological and industrial services, research and design
Goods & Services
Advertising services; advertising services, namely, placement, and dissemination of online advertising; advertising campaign management services in the nature of tracking, analyzing, and reporting on consumer data, demographics, behavioral information, visits to websites, consumption of media, and responses to advertisements; mediation of advertising; business marketing, promotions, and advertising consulting services; conducting market research and consumer research. Providing online non-downloadable software for tracking, managing, and optimizing advertising and promotional campaigns, and calculating return on investment in connection with the same; providing online non-downloadable software for tracking website traffic, e-commerce activity, customer loyalty, and sales conversion rates; Software-as-a-service (SaaS) services in the field of digital media measurement, website audience analysis and advertising optimization, hosting software that manages, monitors, tracks, and optimizes the performance and effectiveness of online and offline marketing campaigns; Software as a service (SAAS) services, featuring software for personalization, content targeting, behavioral targeting, and segmentation.
64.
Quantifying mobility of mobile devices via a privacy preserving mobility metric
Embodiments of the invention generate metrics quantifying the mobility of a mobile device without persisting information related to the device's specific location at any given time. Specifically, at multiple intervals, a value of a mobility metric is computed based on the distance between the current location of the mobile device and a previously identified origin location of the mobile device. The values of the mobility metric computed over a period of time quantify the overall mobility of the mobile device. The mobility metric does not provide any information regarding the specific location of the mobile device at any given time.
H04W 4/02 - Services making use of location information
H04W 64/00 - Locating users or terminals for network management purposes, e.g. mobility management
G01S 5/02 - Position-fixing by co-ordinating two or more direction or position-line determinationsPosition-fixing by co-ordinating two or more distance determinations using radio waves
H04W 8/02 - Processing of mobility data, e.g. registration information at HLR [Home Location Register] or VLR [Visitor Location Register]Transfer of mobility data, e.g. between HLR, VLR or external networks
H04L 29/08 - Transmission control procedure, e.g. data link level control procedure
H04W 4/029 - Location-based management or tracking services
G01S 5/00 - Position-fixing by co-ordinating two or more direction or position-line determinationsPosition-fixing by co-ordinating two or more distance determinations
65.
Distributing data of multiple logically independent file systems in distributed storage systems including physically partitioned disks
A distributed storage system maintains multiple logically independent file systems. Each file system includes a data set stored by a storage device of the distributed storage system. During operation, access pattern levels for the multiple logically independent file systems are determined. Thereafter, the data sets included in the multiple logically independent file systems are redistributed across multiple storage devices of the distributed storage. Redistribution of a particular data set is based at least in part on the particular file system including the particular data set and on the determined access pattern levels for the multiple logically independent file systems. In addition, each disk of a plurality of disks in the distributed storage includes a physically separated partition dedicated to storing the data of the file system that is most frequently accessed. The distribution of data is based at least in part on the presence of the physically separated partition.
G06F 3/06 - Digital input from, or digital output to, record carriers
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database systemDistributed database system architectures therefor
66.
Incremental model training for advertisement targeting using streaming data
Incremental model training for advertisement targeting is performed using streaming data. A model for targeting advertisements of an advertising campaign is initialized. A data stream including data corresponding to converters and data corresponding to non-converters is received. The model is then applied to the data corresponding to the converter and data corresponding to the non-converter (or other ratio of converter to non-converters) to obtain a predicted score for each. The predicted score is compared to the observed score (e.g., an observed score of 1 for a converter, and 0 for a non-converter). The difference between the predicted and observed scores is computed, and the model is incrementally updated based on this difference. Models can optionally be built separately on multiple modeling servers that are geographically dispersed in order to support bidding on advertising opportunities in a real-time bidding environment.
A column set server adapts to data use patterns by data consumers by modifying how a table produced by a data producer is partitioned into separate column sets to reduce the waste incurred in accessing the data by multiple consumers of the data. For example, the column set server adjusts a column set distribution when a new consumer process is added, when one is retired, or when relative data set size ratios change.
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database systemDistributed database system architectures therefor
68.
Automated load-balancing of partitions in arbitrarily imbalanced distributed mapreduce computations
A distributed computing system executes a MapReduce job on streamed data that includes an arbitrary amount of imbalance with respect to the frequency distribution of the data keys in the dataset. A map task module maps the dataset to a coarse partitioning, and generates a list of the top K keys with the highest frequency among the dataset. A sort task module employs a plurality of sorters to read the coarse partitioning and sort the data into buckets by data key. The values for the top K most frequent keys are separated into single-key buckets. The other less frequently occurring keys are assigned to buckets that each have multiple keys assigned to it. Then, more than one worker is assigned to each single-key bucket. The output of the multiple workers assigned to each respective single-key bucket is stitched together.
G06F 16/00 - Information retrievalDatabase structures thereforFile system structures therefor
G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database systemDistributed database system architectures therefor
69.
Selective regulation of information transmission from mobile applications to third-party privacy compliant target systems
Selective regulation of information transmission from mobile applications to a third-party privacy compliant target system. A privacy policy is configured for and mapped to each of a multiplicity of mobile application concerns, with each privacy policy comprising rules regulating the transmission of information to a third-party privacy compliant target system. Instrumentation instructions can be integrated with a mobile application and provided to a mobile device. The instrumentation instructions direct the mobile application to submit a privacy policy request comprising a mobile application identifier from the mobile device to a third-party privacy compliance system and enable sending information from the mobile device to the third-party privacy compliant target system, subject to the privacy policy. The privacy policy request is received at the third-party privacy compliance system which selects the privacy policy based on an application identifier and sends the privacy policy to the mobile device for implementation.
A mobile device's location and identifier corresponding to the mobile device is received. The mobile device's location is mapped to a plurality of landmarks proximate to the mobile device's location. The proximate landmarks are stored in association with the mobile device's identifier in a geo data store, and the received location data is then discarded. These steps are iterated over time to build up a data store that can be represented as a frequency distribution of the landmarks that surround mobile devices. Such a frequency distribution can be built for each of a plurality of mobile devices, without maintaining records of any mobile device's location.
A distributed system is adapted to manage the performance of distributed processes. In one aspect, multiple stripes associated with a data item are stored in a distributed storage. The stored stripes include one or more stripes of redundancy information for the data item. A distributed process including at least one task is performed. During performance of the distributed process, a determination is made as to whether to perform an accelerated data retrieval operation. Responsive to a determination to perform an accelerated data retrieval operation, at least one of the one or more stripes of redundancy information for the data item is requested from the distributed storage. Other stripes associated with the data item may also be requested from the distributed storage. After a sufficient subset of stripes associated with the data item is received, the data item is reconstructed using the subset.
G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
G06F 11/10 - Adding special bits or symbols to the coded information, e.g. parity check, casting out nines or elevens
G06F 3/06 - Digital input from, or digital output to, record carriers
Online advertising campaigns are operated responsive to keyword trends. The keywords used by a group of browsers is analyzed periodically over time. A list of the most frequently used keywords is separated into those that have previously appeared on the list, referred to herein as the stable keywords, and those that are newly emerging, referred to herein as the trending keywords. The advertiser selects at least one advertising creative that the advertiser associates with the stable keywords, referred to herein as the stable creative, and at least one advertising creative that the advertiser associates with the trending keywords, referred to herein as the trendy creative. The advertising system then operates the online advertising campaign to deliver the respective stable and trendy creatives in proportion to the frequency of use of the trending versus the stable keywords.
Privacy centric feature analysis. A secure set of multiple mapped features is selected and provided to a mobile device. Each mapped feature maps a sharable feature to a matching criterion for an item of protected information and no combination of mapped features for a secure set are unique to an individual item of protected information. Privacy compliance instructions enable the mobile device to select a mapped feature from a received set of mapped features by identifying an item of protected information available to the mobile device which corresponds to a matching criterion found in the received set of mapped features. The sharable feature of the selected mapped feature is identified and sent to a privacy compliant destination. Advantageously, the analysis system protects the privacy of the mobile device user because it does not require the mobile device to relay protected information for the selection of customized content or relevant advertisements.
Adaptive Sampling. Data comprising pairings of data value with lists of data keys are received. The range of possible values of the data keys is partitioned into unbalanced buckets, with at least two of the unbalanced buckets representing different fractions of the range. Each unbalanced bucket is assigned to a respective processing unit selected from a plurality of processing units. The pairings are processed by the processing units, with each processing unit generating an intermediate result. The intermediate results are combined to generate a comprehensive result. A sampling error is determined by scaling an unbalanced bucket's intermediate result according to its corresponding fraction and comparing the scaled intermediate result to the comprehensive result. An unbalanced bucket having a sampling error less than a sampling error threshold is selected. The selected unbalanced bucket's corresponding fraction is selected as a sampling rate for a second data processing job.
Automatic performance triggered campaign adjustment. A hierarchical feature tree is generated. Each child node's feature is more specific than its respective parent node's feature. The discovery system creates a behavioral model comprising features of the feature tree which is used in the operation of an advertising campaign. A degraded model feature is detected at the discovery system by comparing a performance metric of a model feature from two different time windows. The discovery system matches a node of the feature tree with the degraded feature and selects a prospective model feature from an ancestor node of the matching feature's node. An estimated performance metric for the prospective model feature is determined and the results are used to decide if the prospective model feature should be incorporated into an updated model or not. The model can be updated with a new model feature selected from one or more prospective model features.
Protected audience selection system. Media consumption histories of browsers which have converted are received at a modeling system where targeting of browsers has been disabled by excluding targeting labels. A model is built by determining a frequency of each respective media consumption event among the histories and comparing each determined frequency of a respective media consumption event to a frequency of the respective media consumption event among a population of browsers without the conversion event. The model is sent to a targeting system which excludes conversion events. A description of the conversion event is received at the targeting system. A history of a targetable browser is received at the targeting system. The model is applied to the history of the targetable browser at the targeting system in the absence of records of conversion events. Advertising content is sent to the targetable browser according to a result of applying the model.
Preserving privacy related to networked media consumption activity. Source privacy zones are defined and associated with privacy standards Privacy standards include frequency criteria governing the storage of datasets including information associated with networked media consumption activity collected from the source privacy zone. Transaction requests including a networking protocol address are received over a network from a client device at a target location by a networked privacy system. The source privacy zone associated with the client device is identified. Using the networking protocol address to access characteristics having characteristic value(s), a dataset can be created including associating the networked media consumption activity with the characteristic and characteristic value(s). The dataset is pre-processed to comply with the privacy standards. The networking protocol address is discarded. The pre-processed dataset can be stored in a filtered database on a physical storage device at a storage location coupled to the networked privacy system.
A computer-implemented method for conversion timing inference. A conversion timing model is model is configured to predict a likelihood of conversion based on an entity's elapsed time since a qualified entry event. The conversion timing model is constructed based on a distribution of the conversion timespans of converters. Each conversion timespan describes a length of time between a qualified entry event and a conversion event for a converted entity. A notification of an opportunity to expose a candidate entity to networked content is received and the likelihood of conversion for the candidate entity is determined by: determining an elapsed time since a qualified entry event for the candidate entity and applying the conversion timing model to the elapsed time. A response to the notification based on the likelihood of conversion for the candidate entity is prepared. Timely responses may include the selection of customized content, customized advertising content or bid values.
Encouraging broader engagement with a target publisher's content by balancing on-site topic engagement. Responsive to receiving notification of a recipient's request of an item of content from the target publisher, the on-site and off-site content consumption history of the recipient is analyzed. For each of a plurality of topics, historic engagement with on-site and off-site content is measured. Deficient topics having better off-site engagement than on-site engagement are detected. Supplemental content comprising links to items of content available from the target publisher which are characterized by deficient topics is selected and sent to the recipient. In an embodiment, the supplemental content comprises a plurality of links to other web pages on the target publisher's website which are sent to the recipient browser before the requested item of content finishes loading.
Automatic performance triggered model adjustment. A hierarchical feature tree is generated. Each child node's feature is more specific than its respective parent node's feature. A behavioral model comprising features of the feature tree is created and used in the operation of an advertising campaign. A degraded model feature is detected at the discovery system by comparing a performance metric of a model feature from two different time windows. The discovery system matches a node of the feature tree with the degraded feature and selects a prospective model feature from a same-level node or from a lower level node than the matching feature's node. An estimated performance metric for the prospective model feature is determined and the results are used to decide if the model should be updated to include the prospective model feature. The campaign can be operated with the automatically updated model.
An audience selection system for the selection of an entity, based on an entity's consumption history without requiring the storage of a content descriptor for identifying content previously accessed by the entity. By directly and/or indirectly observing the usage of words used to locate content through a search engine over time for a population, a list of depersonalized keywords can be discovered, creating the ability to characterize content based on depersonalized keywords. A protected consumption history can be recorded for an entity using depersonalized keywords instead of recording a content descriptor for identifying the content. Depersonalized keywords do not uniquely identify content. Associating depersonalized keywords with an entity does not mean that the entity has used those depersonalized keywords; it only means that the entity has accessed content which has been accessed in the past by other entities in a population using the depersonalized keywords.
A distributed system processing a publisher's streaming data. The distributed system comprises multiple workers and publisher data stores, each publisher data store dedicated to a worker and a publisher. A sampling ratio (the fraction of data items for storage in the publisher's data store) is selected by a publisher data store's worker based on historical information. At least two workers select different sampling ratios. Data items representing an interaction between an entity and the publisher are received. Each data item is assigned to a worker for processing. A hash function is applied to the data item's identifier, resulting in a key value falling within the hash function's range. The scope of the publisher's data store is equal to the hash function's range multiplied by the sampling ratio of the publisher's data store. A data item with a key value within the scope of the publisher's data store is stored therein.
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & Services
Downloadable software for use by website publishers for collecting, managing, and implementing website visitor data; downloadable software for use by website publishers to enable compliance with regulations regarding website visitor data. Providing online non-downloadable software design tools for creation of software for use by website publishers for collecting and managing website visitor data; providing online non-downloadable software design tools for creation of software for use by website publishers to enable compliance with regulations regarding website visitor data.
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & Services
Downloadable software for use by website publishers for collecting, managing, and implementing website visitor data; downloadable software for use by website publishers to enable compliance with regulations regarding website visitor data Providing online non-downloadable software design tools for creation of software for use by website publishers for collecting and managing website visitor data; providing online non-downloadable software design tools for creation of software for use by website publishers to enable compliance with regulations regarding website visitor data
85.
Characterizing an entity in an identifier space based on behaviors of unrelated entities in a different identifier space
Models are built based on existing histories in one identifier space to infer features of entities in a different identifier space. A source model is built using features of an archetypical population in a given identifier space and the standard population. A join panel, i.e., a set of entities operating across both the given identifier space and a second disjoined identifier space, is scored using the source model. Based on the scores and features associated with the entities in the join panel within the second identifier space, a target model specific to the second identifier space is built. An audience of entities within the second identifier space can then be scored using the target model to identify entities that are similar to the archetypical population.
H04N 21/462 - Content or additional data management e.g. creating a master electronic program guide from data received from the Internet and a Head-end or controlling the complexity of a video stream by scaling the resolution or bit-rate based on the client capabilities
Method and system for assessing the suitability of an entity using a proxy. A description of a behavior associated with a desirable audience is received. A proxy behavior estimated to be characteristic of the desirable audience is selected. The proxy behavior comprises the performance of proxy events related to the consumption of media received by an entity over a network, which can be found in an entity's consumption history. An entity can be assessed for inclusion in a proxy audience, by examining the entity's consumption history for proxy behaviors. A behavioral model is built using a training set comprising the proxy audience. By applying the behavioral model to the consumption history of a specified entity, the specified entity's suitability for selection can be determined. Advantageously, in an embodiment, the invention enables the use of behavioral modeling techniques even when the complete behavior of the desirable audience is not available.
Selective regulation of information transmission from mobile applications to a third-party privacy compliant target system. A privacy policy is configured for and mapped to each of a multiplicity of mobile application concerns, with each privacy policy comprising rules regulating the transmission of information to a third-party privacy compliant target system. Instrumentation instructions can be integrated with a mobile application and provided to a mobile device. The instrumentation instructions direct the mobile application to submit a privacy policy request comprising a mobile application identifier from the mobile device to a third-party privacy compliance system and enable sending information from the mobile device to the third-party privacy compliant target system, subject to the privacy policy. The privacy policy request is received at the third-party privacy compliance system which selects the privacy policy based on an application identifier and sends the privacy policy to the mobile device for implementation.
Privacy centric feature analysis. A secure set of multiple mapped features is selected and provided to a mobile device. Each mapped feature maps a sharable feature to a matching criterion for an item of protected information and no combination of mapped features for a secure set are unique to an individual item of protected information. Privacy compliance instructions enable the mobile device to select a mapped feature from a received set of mapped features by identifying an item of protected information available to the mobile device which corresponds to a matching criterion found in the received set of mapped features. The sharable feature of the selected mapped feature is identified and sent to a privacy compliant destination. Advantageously, the analysis system protects the privacy of the mobile device user because it does not require the mobile device to relay protected information for the selection of customized content or relevant advertisements.
Embodiments of the invention generate metrics quantifying the mobility of a mobile device without persisting information related to the device's specific location at any given time. Specifically, at multiple intervals, a value of a mobility metric is computed based on the distance between the current location of the mobile device and a previously identified origin location of the mobile device. The values of the mobility metric computed over a period of time quantify the overall mobility of the mobile device. The mobility metric does not provide any information regarding the specific location of the mobile device at any given time.
A distributed system is adapted to manage the performance of distributed processes. In one aspect, multiple stripes associated with a data item are stored in a distributed storage. The stored stripes include one or more stripes of redundancy information for the data item. A distributed process including at least one task is performed. During performance of the distributed process, a determination is made as to whether to perform an accelerated data retrieval operation. Responsive to a determination to perform an accelerated data retrieval operation, at least one of the one or more stripes of redundancy information for the data item is requested from the distributed storage. Other stripes associated with the data item may also be requested from the distributed storage. After a sufficient subset of stripes associated with the data item is received, the data item is reconstructed using the subset.
G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
G06F 11/10 - Adding special bits or symbols to the coded information, e.g. parity check, casting out nines or elevens
G06F 3/06 - Digital input from, or digital output to, record carriers
91.
Predicting advertisement impact for audience selection
An influence system for predicting advertisement impact for audience selection. An advertising probe campaign is operated by sending an advertisement to each entity in a treatment group of entities. A control group of entities which excludes the treatment group entities is selected and no campaign advertising content is sent to the treatment group entities. An influence model is created by comparing features of the treatment group converters to features of the control group converters. An individual frequency cap is selected for each entity that is a candidate for the advertising campaign based on a result of applying the influence model to the features of the candidate entity. The entity may be selected to receive an advertisement based on the individual frequency cap. Some embodiments are integrated with a real time bidding (RTB) exchange and a bid response may be configured based on the results of applying the influence model.
Preserving privacy related to networked media consumption activity. Source privacy zones are defined and associated with privacy standards. Privacy standards include frequency criteria governing the storage of datasets including information associated with networked media consumption activity collected from the source privacy zone. Transaction requests including a networking protocol address are received over a network from a client device at a target location by a networked privacy system. The source privacy zone associated with the client device is identified. Using the networking protocol address to access characteristics having characteristic value(s), a dataset can be created including associating the networked media consumption activity with the characteristic and characteristic value(s). The dataset is pre-processed to comply with the privacy standards. The networking protocol address is discarded. The pre-processed dataset can be stored in a filtered database on a physical storage device at a storage location coupled to the networked privacy system.
A distributed system is adapted to manage the performance of distributed processes. In one aspect, multiple stripes associated with a data item are stored in a distributed storage. The stored stripes include one or more stripes of redundancy information for the data item. A distributed process including at least one task is performed. During performance of the distributed process, a determination is made as to whether to perform an accelerated data retrieval operation. Responsive to a determination to perform an accelerated data retrieval operation, at least one of the one or more stripes of redundancy information for the data item is requested from the distributed storage. Other stripes associated with the data item may also be requested from the distributed storage. After a sufficient subset of stripes associated with the data item is received, the data item is reconstructed using the subset.
G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
G06F 11/10 - Adding special bits or symbols to the coded information, e.g. parity check, casting out nines or elevens
G06F 3/06 - Digital input from, or digital output to, record carriers
94.
Redistributing data in a distributed storage system based on attributes of the data
Accesses to a number of data blocks stored in a distributed storage are observed. Following observation of the accesses, the stored data blocks are redistributed. In one aspect, redistribution of the data blocks includes determining the access patterns for one or more of the data blocks based on the observed accesses, and determining the storage sizes for the one or more data blocks. Thereafter, based on the determined access patterns and determined storage sizes, the one or more data blocks are sorted. Subsequently, the one or more data blocks are redistributed or rebalanced across a number of storage devices of the distributed storage based on the sorting. In one aspect, the one or more data blocks are redistributed according to either a uniform distribution scheme or a proportional distribution scheme.
An adaptive bidder for networked advertising. A bid request is received from an exchange over a network. Each bid request represents the opportunity to bid on an advertising opportunity. A processing time limit is determined based at least in part on a network latency measurement, an exchange reported timeout and a bid response buffer. The network latency measurement may be required to meet a freshness standard. The bid response buffer represents the time allotted for the adaptive bidding system to generate a response based on one or more partial results. The exchange reported timeout value can be included in the bid request, and can vary from bid request to bid request. The execution of one or more tasks is initiated by the adaptive bidding system, and each task can make a partial result available. In some cases, a partial result is a cumulative result. A response is determined from one or more partial results which are available before the processing time limit expires. The response is provided to the exchange.
Selective regulation of information transmission from mobile applications to a third-party privacy compliant target system. A privacy policy is configured for and mapped to each of a multiplicity of mobile application concerns, with each privacy policy comprising rules regulating the transmission of information to a third-party privacy compliant target system. Instrumentation instructions can be integrated with a mobile application and provided to a mobile device. The instrumentation instructions direct the mobile application to submit a privacy policy request comprising a mobile application identifier from the mobile device to a third-party privacy compliance system and enable sending information from the mobile device to the third-party privacy compliant target system, subject to the privacy policy. The privacy policy request is received at the third-party privacy compliance system which selects the privacy policy based on an application identifier and sends the privacy policy to the mobile device for implementation.
Embodiments of the invention generate metrics quantifying the mobility of a mobile device without persisting information related to the device's specific location at any given time. Specifically, at multiple intervals, a value of a mobility metric is computed based on the distance between the current location of the mobile device and a previously identified origin location of the mobile device. The values of the mobility metric computed over a period of time quantify the overall mobility of the mobile device. The mobility metric does not provide any information regarding the specific location of the mobile device at any given time.
A column set server adapts to data use patterns by data consumers by modifying how a table produced by a data producer is partitioned into separate column sets to reduce the waste incurred in accessing the data by multiple consumers of the data. For example, the column set server adjusts a column set distribution when a new consumer process is added, when one is retired, or when relative data set size ratios change.
Privacy centric feature analysis. A secure set of multiple mapped features is selected and provided to a mobile device. Each mapped feature maps a sharable feature to a matching criterion for an item of protected information and no combination of mapped features for a secure set are unique to an individual item of protected information. Privacy compliance instructions enable the mobile device to select a mapped feature from a received set of mapped features by identifying an item of protected information available to the mobile device which corresponds to a matching criterion found in the received set of mapped features. The sharable feature of the selected mapped feature is identified and sent to a privacy compliant destination. Advantageously, the analysis system protects the privacy of the mobile device user because it does not require the mobile device to relay protected information for the selection of customized content or relevant advertisements.
