Abstract: 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.

Abstract: A reporting system for providing reports on consumption rate changes for media content delivered over a network. A respective media consumption history is received for each of a plurality of entities at a storage. The histories are analyzed to identify selected media content for reporting based on changes in a consumption rate of the media content between at least two time intervals. A report including a reference to the selected media content is provided to a system. In an example, the system is a search engine indexing system and the invention enables the rapid indexing of new content and/or media content experiencing a surge in popularity. The consumption rate changes can be measured for monitored audiences comprising a subset of the audience. The monitored audience can be provided as a list of entities and/or selected based on the media consumption history and/or similarity to a known set of entities.

Abstract: 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.

Abstract: A method and system for triggering multiple client requests, including: providing directions for obtaining multibeacon instructions, in response to a content request from the client device, providing the multibeacon instructions in response to a request from the client device, with the request for multibeacon instructions submitted by the client device based on the directions, receiving an initial image request at the multibeacon management system from the client device wherein the initial image request is submitted by the client device upon execution of the multibeacon instructions, and, composing and sending a beacon from the multibeacon management system to the client device in response to the initial image request causing the configuration of a storage device at the client device for storing the beacon, wherein the properties of the beacon are configured to trigger the multibeacon instructions to instruct the client device to submit additional image requests to the multibeacon management system.

Abstract: 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.

Abstract: A tracking identifier synchronization system using a convergent selection method comprises first party instructions accessed through a content provider and a synchronization system comprising a receiver, a composer and an output. First party instructions direct the client to submit a request comprising a third party cookie to a synchronization system. The composer generates setting instructions for execution at the client. Setting instructions comprise instructions to use a client-executed convergent selection method to select values first party cookies and, optionally, reporting instructions directing the client to transmit the values of client tracking identifiers. Repeated invocation of client-executed convergent selection methods results in the convergence of cookie values for many operational cases.

Abstract: A method, system and computer readable storage medium for reporting on a measured change in a consumption rate. Media consumption histories for a plurality of entities are received. A monitored audience is selected from the plurality of entities by selecting entities which have completed an online purchase. A category value for each of two or more categories of media content is determined. One category of media content includes one or more items of media content. One category value represents the measured change in consumption rate for one category of media content for the monitored audience between at least two time intervals. One consumption rate is determined based on the number of times each item of media content in the one category has been delivered over a network during one time interval. A report including a reference to two or more categories and their associated category values is generated.

Abstract: A method, system and computer readable storage medium for reporting on a measured change in a consumption rate. Media consumption histories for a plurality of entities are received. A monitored audience is selected from the plurality of entities by selecting entities which have completed an online purchase. A category value for each of two or more categories of media content is determined. One category of media content includes one or more items of media content. One category value represents the measured change in consumption rate for one category of media content for the monitored audience between at least two time intervals. One consumption rate is determined based on the number of times each item of media content in the one category has been delivered over a network during one time interval. A report including a reference to two or more categories and their associated category values is generated.