This disclosure describes machine learning techniques to automatically remove, reorder, or prioritize segments of content such that users can quickly access information that is new to them. With user permission, data such as user profile, historical content consumption patterns and its relevance, etc. is obtained. This data is used to chunk and rank historical content segments based on relevance to the user. A machine learning model is trained to identify new content (or segments thereof) based on the knowledge gain that the content is likely to provide to the user.
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Cărbune, Victor and Damian, Alexandru, "Recommending content based on anticipated knowledge gain", Technical Disclosure Commons, (June 11, 2019)