System and method for neighborhood optimization for content recommendation
First Claim
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1. A method for recommending content to a home system for display of the content on a display device of the home system, comprising:
- defining a neighborhood of other users using the cost function;
based on the neighborhood, providing at least one content recommendation to a user of the home system.
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Abstract
A cost function is stochastically optimized using, e.g., simulated annealing to render a neighborhood of entities based on which content recommendations can be provided to a user of a home entertainment system. The cost function represents a normalized sum of rating similarity scores from entities of the neighborhood that are related to content items viewed by the user.
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Citations
20 Claims
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1. A method for recommending content to a home system for display of the content on a display device of the home system, comprising:
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defining a neighborhood of other users using the cost function; based on the neighborhood, providing at least one content recommendation to a user of the home system. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A system receiving ratings from entities that collectively comprise potential neighbors of a subject user in a neighborhood and returning content recommendations to the subject user at least partially based thereon, comprising:
at least one server programmed to stochastically establish a pseudo-optimum neighborhood based at least in part on the ratings, and to return content recommendations at least partially based on the neighborhood. - View Dependent Claims (9, 10, 11, 12, 13, 14)
- 15. A computer iteratively computing a cost function representing a sum of rating similarity scores from entities of a neighborhood of a home entertainment system and related to content items viewed by a user of the home entertainment system, the neighborhood being used to recommend content to the user of the home entertainment system.
Specification