Method and system for recommending content

Interactive video distribution systems – Program – message – or commercial insertion or substitution – Specific to individual user or household

Reexamination Certificate

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Reexamination Certificate

active

07434244

ABSTRACT:
Provided are a method and system for recommending content. The method and system enable a user to be given recommendations of contents similar to what he/she likes. The method for recommending content includes creating a user profile according to a predetermined model based on a user's reaction to the content, obtaining content features from one or more data sources, and creating a list of recommended contents according to a predetermined process based on the user profile and the content features. The system for recommending content includes a user profiling module that creates user profiles according to a predetermined model based on a user's reaction to the content, a digital television module that obtains content metadata from one or more data sources, and a content rating module that creates a list of recommended contents based on the user profile and the content metadata received from the user profiling module and the digital television module. The user can be given recommendations of contents similar to what he/she likes.

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Beerud Dilip Sheth, “A Learning Approach to Personalized Information Filtering”, Massachusetts Institute of Technology Feb. 1994.

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