Media content discovery and character organization techniques

• US 10,642,882 B2
• Filed: 10/17/2017
• Issued: 05/05/2020
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: The Nielsen Company LLC (MOOD Media Corporation)
• Original Assignee: The Nielsen Company LLC (MOOD Media Corporation)
• Inventors: Payne, Rachel, Bhatt, Meghana, Mohanty, Natasha
• Primary Examiner(s): Nguyen, Phong H
• Application Number:
  US15/786,351
• Publication Number:
  US 20180137122A1
• Time in Patent Office: 931 Days
• Field of Search: 707722, 707734, 707748
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/3334 Selection or weighting of terms from queries, including natural language queries
• CPC Class Codes: G06F 16/43 Querying
• CPC Class Codes: G06F 16/435 Filtering based on additional data, e.g. user or group profiles
• CPC Class Codes: G06F 16/44 Browsing; Visualisation therefor
• CPC Class Codes: G06F 16/48 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
• CPC Class Codes: G06F 16/68 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
• CPC Class Codes: G06F 16/78 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
• CPC Class Codes: G06F 16/7867 using information manually generated, e.g. tags, keywords, comments, title and artist information, manually generated time, location and usage information, user ratings

Abstract

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.

Claims

1. A computer-implemented method of recommending media content, the method comprising:

accessing a first preference coefficient associated with a 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 first character rating of a first character appearing in a media content based on (i) the first preference coefficient and a first attribute value of the first character corresponding to the first character attribute and (ii) the second preference coefficient and a second attribute value of the first character corresponding to the second character attribute;

calculating a second character rating of a second character appearing in the media content based on (i) the first preference coefficient and a first attribute value of the second character corresponding to the first character attribute and (ii) the second preference coefficient and a second attribute value of the second character corresponding to the second character attribute;

calculating a media content rating for the media content 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:

accessing the first attribute value of the first character and the second attribute value of the first character from a character model of the first character.

3. The computer-implemented method of claim 2, further comprising:

determining the first attribute value 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 the first character attribute; and

updating the first attribute value of the first character based on the plurality of attribute terms.

4. The computer-implemented method of claim 3, wherein

each of the at least some of the plurality of attribute terms is associated with a corresponding strength value;

and

updating the first attribute value of the first character is based on the corresponding strength values.

5. The computer-implemented method of claim 3, further comprising:

storing the updated first attribute value of the first character in a database as a vector, the vector associated with the first character.

6. 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 that the media content rating is greater than the minimum content rating value.

7. The computer-implemented method of claim 2, wherein:

a character preference function comprises a 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 character attributes; and

calculating the first character rating of the first character further comprises determining a product of multiplying the at least one of the plurality of preference coefficients with each attribute value of a first plurality of attribute values of the two or more character attributes of interest.

8. A non-transitory computer-readable storage medium comprising computer-executable instructions for recommending media content, the computer-executable instructions comprising instructions for:

accessing a first preference coefficient associated with a 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 first character rating of a first character appearing in a media content based on (i) the first preference coefficient and a first attribute value of the first character corresponding to the first character attribute and (ii) the second preference coefficient and a second attribute value of the first character corresponding to the second character attribute,

calculating a second character rating of a second character appearing in a media content based on (i) the first preference coefficient and a first attribute value of the second character corresponding to the first character attribute and (ii) the second preference coefficient and a second attribute value of the second character corresponding to the second character attribute,

calculating a media content rating for the media content 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.

9. The non-transitory computer-readable storage medium of claim 8, further comprising instructions for:

accessing the first attribute value of the first character and the second attribute value of the first character from a character model of the first character.

10. The non-transitory computer-readable storage medium of claim 9, further comprising instructions for:

determining the first attribute value 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 the first character attribute; and

updating the first attribute value of the first character based on the plurality of attribute terms.

11. The non-transitory computer-readable storage medium of claim 10, wherein

each of the at least some of the plurality of attribute terms is associated with a corresponding strength value;

and

updating the first attribute value of the first character is based on the corresponding strength values.

12. The non-transitory computer-readable storage medium of claim 10, further comprising instructions for:

storing the updated first attribute value of the first character in a database as a vector, the vector associated with the first character.

13. The non-transitory computer-readable storage medium of claim 8, 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 that the media content rating is greater than the minimum content rating value.

14. The non-transitory computer-readable storage medium of claim 9, wherein:

a character preference function comprises a 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 character attributes; and

calculating the first character rating of the first character further comprises determining a product of multiplying the at least one of the plurality of preference coefficients with each attribute value of a first plurality of attribute values of the two or more character attributes of interest.

15. An apparatus for recommending media content, the apparatus comprising:

a memory; and

one or more computer processors configured to;

access a first preference coefficient associated with a 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;

calculate a first character rating of a first character appearing in a media content based on (i) the first preference coefficient and a first attribute value of the first character corresponding to the first character attribute and (ii) the second preference coefficient and a second attribute value of the first character corresponding to the second character attribute;

calculate a second character rating of a second character appearing in a media content based on (i) the first preference coefficient and a first attribute value of the second character corresponding to the first character attribute and (ii) the second preference coefficient and a second attribute value of the second character corresponding to the second character attribute;

calculate a media content rating for the media content based on the first character rating and the second character rating; and

select, based on the media content rating, the media content from among a plurality of media contents.

16. The apparatus of claim 15, the one or more computer processors further configured to:

access the first attribute value of the first character and the second attribute value of the first character from a character model of the first character.

17. The apparatus of claim 16, the one or more computer processors further configured to:

determine the first attribute value 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 the first character attribute; and

updating the first attribute value of the first character based on the plurality of attribute terms.

18. The apparatus of claim 17, wherein:

each of the at least some of the plurality of attribute terms is associated with a corresponding strength value; and

updating the first attribute value of the first character is based on the corresponding strength values.

19. The apparatus of claim 17, the one or more computer processors further configured to:

store the updated first attribute value of the first character in a database as a vector, the vector associated with the first character.

20. The apparatus of claim 15, 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 that the media content rating is greater than the minimum content rating value.

21. The apparatus of claim 16, wherein:

a character preference function comprises a 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 character attributes; and

calculating the first character rating of the first character further comprises determining a product of multiplying the at least one of the plurality of preference coefficients with each attribute value of a first plurality of attribute values of the two or more character attributes.