CPC G06F 16/435 (2019.01) [G06F 16/24578 (2019.01); G06F 16/3334 (2019.01); G06F 16/43 (2019.01); G06F 16/44 (2019.01); G06F 16/48 (2019.01); G06F 16/7867 (2019.01); G06F 16/68 (2019.01); G06F 16/78 (2019.01)] | 17 Claims |
1. A method of recommending media content performed by a computing system comprising a processor and a memory, the method comprising:
storing, in the memory, a character preference function that is associated with a user of the computing system and that identifies preference coefficients that indicate character attributes of interest to the user;
accessing the character preference function stored in the memory to determine a first preference coefficient associated with the user and a second preference coefficient associated with the user, wherein the first preference coefficient is indicative of a degree of preference of the user regarding a first character attribute, and wherein the second preference coefficient is indicative of a degree of preference of the user regarding a second character attribute;
calculating a character rating of a character appearing in a media content based on the first preference coefficient, a first attribute value of the character corresponding to the first character attribute, the second preference coefficient, and a second attribute value of the character corresponding to the second character attribute;
calculating a media content rating for the media content based on the character rating, wherein the media content rating for the media content is further based on a salience value for the character, and wherein the salience value for the character is based on a number of reactions detected in social media relating to the character;
selecting, based on the media content rating, the media content from among a plurality of media contents; and
generating, for display on a display device communicatively coupled to the computing system, a display of the selected media content as recommended content for the user, wherein generating the display of the selected media content comprises recommending, based on the media content rating, the selected media content.
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