Abstract: One aspect of systems and methods for segment size estimation includes identifying a segment of users for a first time period based on time series data, wherein the time series data includes a series of interactions between users and a content channel and wherein the segment includes a portion of the users interacting with the content channel during the first time period; computing a segment return value for a second time period based on the time series data by computing a first subset and a second subset of the segment, wherein the first subset includes users that interact with the content channel greater than a threshold number of times during a range of the time series data and the second subset comprises a complement of the first subset with respect to the segment; and providing customized content to a user in the segment based on the segment return value.

Abstract: Introduced is a technique for assigning attribution values associated with a metric to dimensions in a set of data. An attribution model can be implemented to process data to assign attribution values to the dimensions in the data. The attribution model can be configured accordingly to game theoretic properties such as Shapley value. For example, each of the dimensions in the data may correspond to a different player in a cooperative game based on a specified value function. Using the specified value function, attribution values associated with a metric can be assigned to the dimensions in the data. The introduced technique can be implemented to assign attribution value associated with various types of metric to various types of dimensions. Further, the introduced technique is highly scalable and can be implemented to process data at query time without requiring any offline models to be run.

Abstract: Systems and methods provide for analyzing a group of online articles to identify relevant and popular online articles given a selection of topic(s) and/or term(s). An article score is generated for each online article based on the selected topic(s) and/or term(s) as a function of the relevance of the topic(s) and/or term(s) to the online article and visitor metrics for the online articles. The online articles are ranked based on the article scores, and an indication of the ranked online articles is provided for presentation to the user. In further embodiments, important terms are identified for a selection of topic(s) and/or term(s) based on the most relevant and popular online articles for the selected topics/terms.

Abstract: Systems and methods provide for analyzing a group of online articles to identify relevant and popular topics. Text from each online is analyzed to identify topics relevant to each online article and to generate a relevance score for each topic and each online article. The topics are scored as a function of the relevance scores and visitor metrics for the online articles. The visitor metrics may include all visitors or only visitors within a particular visitor segment. The most relevant and popular topics are identified based on the scored topics. In some embodiments, the online articles are further analyzed to identify terms used in the online articles that are important to each topic. Further embodiments analyze the online articles to determine the lifespan of topics and terms, reflecting the popularity of topics and terms over time intervals.

Abstract: Systems and methods provide for analyzing a group of online articles to identify relevant and popular topics. Text from each online is analyzed to identify topics relevant to each online article and to generate a relevance score for each topic and each online article. The topics are scored as a function of the relevance scores and visitor metrics for the online articles. The visitor metrics may include all visitors or only visitors within a particular visitor segment. The most relevant and popular topics are identified based on the scored topics. In some embodiments, the online articles are further analyzed to identify terms used in the online articles that are important to each topic. Further embodiments analyze the online articles to determine the lifespan of topics and terms, reflecting the popularity of topics and terms over time intervals.

Abstract: Systems and methods provide for analyzing a group of online articles to identify relevant and popular online articles given a selection of topic(s) and/or term(s). An article score is generated for each online article based on the selected topic(s) and/or term(s) as a function of the relevance of the topic(s) and/or term(s) to the online article and visitor metrics for the online articles. The online articles are ranked based on the article scores, and an indication of the ranked online articles is provided for presentation to the user. In further embodiments, important terms are identified for a selection of topic(s) and/or term(s) based on the most relevant and popular online articles for the selected topics/terms.