Media content discovery and character organization techniques
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.
1. A computer-implemented method comprising:
determining, by a computing system, one or more attribute values of a given user;
accessing, by the computing system from a database, character preference functions for a plurality of other users having at least one attribute value in common with the one or more attribute values of the given user, wherein each character preference function comprises information identifying a plurality of preference coefficients, with each preference coefficient of the plurality of preference coefficients associated with a respective attribute of a plurality of attributes;
determining, by the computing system using the character preference functions for the plurality of other users, a character preference function for the given user, wherein the character preference function comprises information identifying a plurality of preference coefficients, with each preference coefficient of the plurality of preference coefficients associated with a respective attribute of a plurality of attributes, wherein determining the character preference function for the given user comprises deriving the character preference function for the given user from statistics indicative of the preference coefficients within the character preference functions for the plurality of other users; and
using, by the computing system, the character preference function for the given user to select one or more media contents from among a plurality of media contents, wherein using the character preference function for the given user to select one or more media contents from among the plurality of media contents comprises determining a character rating for a character in a media content from among the plurality of media contents based on the character preference function for the given user and a character model for the character.
2. The computer-implemented method of claim 1 , wherein the one or more attribute values of the given user comprise a gender, and wherein the at least one attribute value in common is the gender.
3. The computer-implemented method of claim 1 , wherein the one or more attribute values of the given user correspond to an education attribute, and wherein the at least one attribute value in common corresponds to the education attribute.
4. The computer-implemented method of claim 3 , wherein the education attribute comprises a type of degree.
5. The computer-implemented method of claim 1 , wherein determining the character preference function for the given user using the character preference functions for the plurality of other users comprises:
determining that the character preference functions for a majority of users of the plurality of other users include a given preference coefficient having values that are greater than zero; and
designating as the given preference coefficient within the character preference function for the given user a value that is greater than zero.
6. The computer-implemented method of claim 1 , further comprising identifying the plurality of other users having the at least one attribute value in common with the one or more attribute values of the given user.
7. The computer-implemented method of claim 1 , wherein the character model for the character comprises a multidimensional representation of the plurality of attributes.
8. The computer-implemented method of claim 1 , further comprising determining a media content rating for the media content based on the character rating for the character.
9. The computer-implemented method of claim 8 , further comprising recommending the media content to the given user based on the media content rating.
10. The computer-implemented method of claim 1 , further comprising rating a likelihood that the given user will enjoy the media content based on the character preference function for the given user and the character model.
11. A non-transitory computer-readable medium having stored thereon program instructions that upon execution by a processor, cause performance of a set of acts comprising:
determining one or more attribute values of a given user;
accessing, from a database, character preference functions for a plurality of other users having at least one attribute value in common with the one or more attribute values of the given user, wherein each character preference function comprises information identifying a plurality of preference coefficients, with each preference coefficient of the plurality of preference coefficients associated with a respective attribute of a plurality of attributes;
determining, using the character preference functions for the plurality of other users, a character preference function for the given user, wherein the character preference function comprises information identifying a plurality of preference coefficients, with each preference coefficient of the plurality of preference coefficients associated with a respective attribute of a plurality of attributes, wherein determining the character preference function for the given user comprises deriving the character preference function for the given user from statistics indicative of the preference coefficients within the character preference functions for the plurality of other users; and
using the character preference function for the given user to select one or more media contents from among a plurality of media contents, wherein using the character preference function for the given user to select one or more media contents from among the plurality of media contents comprises determining a character rating for a character in a media content from among the plurality of media contents based on the character preference function for the given user and a character model for the character.
12. The non-transitory computer-readable medium of claim 11 , wherein determining the character preference function for the given user using the character preference functions for the plurality of other users comprises:
determining that the character preference functions for a majority of users of the plurality of other users include a given preference coefficient having values that are greater than zero; and
designating as the given preference coefficient within the character preference function for the given user a value that is greater than zero.
13. A computing system comprising a processor coupled to a memory, the computing system configured for performing a set of acts comprising:
determining one or more attribute values of a given user;
accessing, from a database, character preference functions for a plurality of other users having at least one attribute in common with the one or more attribute values of the given user, wherein each character preference function comprises information identifying a plurality of preference coefficients, with each preference coefficient of the plurality of preference coefficients associated with a respective attribute of a plurality of attributes;
determining, using the character preference functions for the plurality of other users, a character preference function for the given user, wherein the character preference function comprises information identifying a plurality of preference coefficients, with each preference coefficient of the plurality of preference coefficients associated with a respective attribute of a plurality of attributes, wherein determining the character preference function for the given user comprises deriving the character preference function for the given user from statistics indicative of the preference coefficients within the character preference functions for the plurality of other users; and
using the character preference function for the given user to select one or more media contents from among a plurality of media contents, wherein using the character preference function for the given user to select one or more media contents from among the plurality of media contents comprises determining a character rating for a character in a media content from among the plurality of media contents based on the character preference function for the given user and a character model for the character.
14. The computing system of claim 13 , wherein determining the character preference function for the given user using the character preference functions for the plurality of other users comprises:
determining that the character preference functions for a majority of users of the plurality of other users include a given preference coefficient having values that are greater than zero; and
designating as the given preference coefficient within the character preference function for the given user a value that is greater than zero.