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 of recommending media content, the method comprising:
accessing 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 plurality of attribute values for the plurality of attributes of a first character of a plurality of characters of a media content;
accessing a second plurality 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 based on the plurality of preference coefficients and the first plurality of attribute values;
calculating a second character rating of the second character based on the plurality of preference coefficients and the second plurality 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
selecting, based on the media content rating, the media content from among a plurality of media contents.
2. The computer-implemented method of claim 1 , further comprising:
determining the first plurality of attribute values in part by:
identifying textual content associated with the first character, the textual content contained in an electronic source;
aggregating a plurality of attribute terms associated with the first character from the textual content;
mapping at least some of the plurality of attribute terms to at least some of the plurality of attributes; and
updating attribute values of the first character based on the plurality of attribute terms.
3. The computer-implemented method of claim 2 , wherein
each of the at least some of the plurality of attribute terms is associated with a corresponding strength value; and
updating attribute values of the first character is based on the corresponding strength values.
4. The computer-implemented method of claim 2 , further comprising:
storing the updated attribute values of the first character in a database as a vector, the vector associated with the first character.
5. The computer-implemented method of claim 1 , further comprising:
accessing a minimum content rating value;
comparing the media content rating to the minimum content rating value, wherein the media content rating is numerical and the minimum content rating value is numerical; and
determining the media content rating is greater than the minimum content rating value.
6. The computer-implemented method of claim 1 , wherein:
a character preference function comprises the plurality of preference coefficients;
the character preference function is a second order function associating at least one of the plurality of preference coefficients with two or more attributes of interest of the plurality of attributes;
calculating the first character rating of the first character further comprises determining the product of multiplying the at least one of the plurality of preference coefficients with each attribute value of the first plurality of attribute values of the two or more attributes of interest of the plurality of attributes; and
calculating the second character rating of the second character further comprises determining the product of multiplying the at least one of the plurality of preference coefficients with each attribute value of the second plurality of attribute values of the two or more attributes of interest of the plurality of attributes.
7. A non-transitory computer-readable storage medium comprising computer-executable instructions for recommending media content, the computer-executable instructions comprising instructions for:
accessing 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 plurality of attribute values for the plurality of attributes of a first character of a plurality of characters of a media content;
accessing a second plurality 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 based on the plurality of preference coefficients and the first plurality of attribute values;
calculating a second character rating of the second character based on the plurality of preference coefficients and the second plurality 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
selecting, based on the media content rating, the media content.
8. The non-transitory computer-readable storage medium of claim 7 , further comprising instructions for:
determining the first plurality of attribute values in part by:
identifying textual content associated with the first character, the textual content contained in an electronic source;
aggregating a plurality of attribute terms associated with the first character from the textual content;
mapping at least some of the plurality of attribute terms to at least some of the plurality of attributes; and
updating attribute values of the first character based on the plurality of attribute terms.
9. The non-transitory computer-readable storage medium of claim 8 , wherein
each of the at least some of the plurality of attribute terms is associated with a corresponding strength value; and
updating attribute values of the first character is based on the corresponding strength values.
10. The non-transitory computer-readable storage medium of claim 8 , further comprising instructions for:
storing the updated attribute values of the first character in a database as a vector, the vector associated with the first character.
11. The non-transitory computer-readable storage medium of claim 7 , further comprising instructions for:
accessing a minimum content rating value;
comparing the media content rating to the minimum content rating value, wherein the media content rating is numerical and the minimum content rating value is numerical; and
determining the media content rating is greater than the minimum content rating value.
12. The non-transitory computer-readable storage medium of claim 7 , wherein:
a character preference function comprises the plurality of preference coefficients;
the character preference function is a second order function associating at least one of the plurality of preference coefficients with two or more attributes of interest of the plurality of attributes;
calculating the first character rating of the first character further comprises determining the product of multiplying the at least one of the plurality of preference coefficients with each attribute value of the first of attribute values of the two or more attributes of interest of the plurality of attributes; and
calculating the second character rating of the second character further comprises determining the product of multiplying the at least one of the plurality of preference coefficients with each attribute value of the second of attribute values of the two or more attributes of interest of the plurality of attributes.
13. An apparatus for recommending media content, the apparatus comprising:
a memory; and
one or more computer processors configured to:
access 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;
access a first plurality of attribute values for the plurality of attributes of a first character of a plurality of characters of a media content;
access a second plurality of attribute values for the plurality of attributes of a second character of the plurality of characters;
calculate a first character rating of the first character based on the plurality of preference coefficients and the first plurality of attribute values;
calculate a second character rating of the second character based on the plurality of preference coefficients and the second plurality of attribute values;
calculate a media content rating, the media content rating calculated based on the first character rating and the second character rating; and
select, based on the media content rating, the media content.
14. The apparatus of claim 13 , the one or more computer processors further configured to:
determine the first plurality of attribute values in part by:
identifying textual content associated with the first character, the textual content contained in an electronic source;
aggregating a plurality of attribute terms associated with the first character from the textual content;
mapping at least some of the plurality of attribute terms to at least some of the plurality of attributes; and
updating attribute values of the first character based on the plurality of attribute terms.
15. The apparatus of claim 14 , wherein:
each of the at least some of the plurality of attribute terms is associated with a corresponding strength value; and
updating attribute values of the first character is based on the corresponding strength values.
16. The apparatus of claim 14 , the one or more computer processors further configured to:
store the updated attribute values of the first character in a database as a vector, the vector associated with the first character.
17. The apparatus of claim 13 , the one or more computer processors further configured to:
access a minimum content rating value;
compare the media content rating to the minimum content rating value, wherein the media content rating is numerical and the minimum content rating value is numerical; and
determine the media content rating is greater than the minimum content rating value.
18. The apparatus of claim 13 , wherein:
a character preference function comprises the plurality of preference coefficients;
the character preference function is a second order function associating at least one of the plurality of preference coefficients with two or more attributes of interest of the plurality of attributes;
calculating the first character rating of the first character further comprises determining the product of multiplying the at least one of the plurality of preference coefficients with each attribute value of the first plurality of attribute values of the two or more attributes of interest of the plurality of attributes; and
calculating the second character rating of the second character further comprises determining the product of multiplying the at least one of the plurality of preference coefficients with each attribute value of the second plurality of attribute values of the two or more attributes of interest of the plurality of attributes.