Methods, systems, and media for recommending content items based on topics

摘要

Mechanisms for recommending content items based on topics are provided. In some implementations, a method for recommending content items is provided that includes: determining a plurality of accessed content items associated with a user, wherein each of the plurality of content items is associated with a plurality of topics; determining the plurality of topics associated with each of the plurality of accessed content items; generating a model of user interests based on the plurality of topics, wherein the model implements a machine learning technique to determine a plurality of weights for assigning to each of the plurality of topics; applying the model to determine, for a plurality of content items, a probability that the user would watch a content item of the plurality of content items; ranking the plurality of content items based on the determined probabilities; and selecting a subset of the plurality of content items to recommend to the user based on the ranked content items.

主权项

1. A method for recommending content items, the method comprising:
determining a plurality of accessed content items associated with a user, wherein each of the plurality of accessed content items is associated with a plurality of topics; generating a user interest model of interactions between the plurality of topics and the plurality of accessed content items, wherein the user interest model (i) determines a plurality of related topics associated with the plurality of topics from the plurality of accessed content items, (ii) generates user interest information associated with the user using at least a portion of the plurality of related topics, (iii) determines similarities between the user interest information associated with the user and user interest information of other users including the at least a portion of the plurality of related topics associated with the user, and (iv) determines a conjunction of between the similarities and the plurality of accessed content items; applying the model to determine, for a plurality of content items, a probability that the user selects a content item from the plurality of content items for presentation; ranking the plurality of content items based on the determined probabilities; and selecting at least one of the plurality of content items to recommend to the user based on the ranked plurality of content items.