Media content discovery and character organization techniques

摘要

Techniques for recommending media are described. A character preference function comprising a plurality of preference coefficients is accessed. A first character model comprises a first set of attribute values for the plurality of attributes of a first character. The first and second characters are associated with a first and second salience value, respectively. A second character model comprises a second set of attribute values for the plurality of attributes of a second character of the plurality of characters. A first character rating is calculated using the plurality of preference coefficients and the first set of attribute values. A second character rating of the second character is calculated using the plurality of preference coefficients with the second set of attribute values. A media rating is calculated based on the first and second salience values and the first and second character ratings. A media is recommended based on the media rating.

主权项

1. A computer-implemented method of recommending media content, the method comprising:
accessing a character preference function of a user, the character preference function comprising information identifying a plurality of preference coefficients, each preference coefficient of the plurality of preference coefficients associated with at least one attribute of interest of a plurality of attributes; accessing a first character model, the first character model comprising information identifying a first set of attribute values for the plurality of attributes of a first character of a plurality of characters appearing in a media content; accessing a second character model, the second character model comprising information identifying a second set of attribute values for the plurality of attributes of a second character of the plurality of characters; calculating a first character rating of the first character by performing a summation of the products of multiplying the plurality of preference coefficients with the first set of attribute values; calculating a second character rating of the second character by performing a summation of the products of multiplying the plurality of preference coefficients with the second set of attribute values; calculating a media content rating, the media content rating calculated based on the first character rating and the second character rating; and recommending the media content to the user based on the media content rating.