Abstract:
Systems and techniques are provided for optimizing personalized recommendations with longitudinal data and a future objective. An identifier may be received for content items. A user content item history including a list identifying a previously acquired content item may be received. Content item metadata may be received including a correlation between the previously acquired content item and a content item for which an identifier was received, and a correlation between a content item for which an identifier was received and fulfillment of a future objective. A joint probability may be determined for each content item based on the user content item history and the content item metadata, including the probability that the content item will be acquired by the user after being recommended to the user and that a future objective will be fulfilled after the content item is acquired by the user.
Abstract:
Systems and methods for providing real-time analysis of feature relationships are provided. In some aspects, a method includes receiving user activity data and user status data for users in the interactive network, the interactive network comprising at least two user features; generating a user dataset by associating, for each user, the user's activity data with the user's status data using a unique identification of the user and a timestamp; analyzing the user dataset using a statistical model; and providing, for display, an output of the analysis by the statistical model, the output including an indicator of a relationship between a use of one of the two user features with a use of the other of the two user features.