TASTE PROFILE ATTRIBUTES

• US 20140279817A1
• Filed: 03/14/2014
• Published: 09/18/2014
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: Spotify AB (Spotify Technology SA)
• Original Assignee: The Echo Nest Corporation (Spotify Technology SA)
• Inventors: Whitman, Brian, Lamere, Paul
• Granted Patent: US 10,540,385 B2
• Time in Patent Office: Days
• US Class Current: 706/52
• CPC Class Codes: G06F 16/437 Administration of user profiles, e.g. generation, initialisation, adaptation, distribution
• CPC Class Codes: G06F 16/637 Administration of user profiles, e.g. generation, initialization, adaptation or distribution

Abstract

Methods, systems and computer program products are provided for summarizing user activity associated with media content by accessing a taste profile containing a representation of media content activity corresponding to at least one of a plurality of items, generating at least one statistic corresponding to the media content activity, and generating a taste profile attribute by using the at least one statistic.

Claims

1. A system for summarizing user activity associated with media content, comprising:

a processor configured to;

access a taste profile containing a representation of media content activity corresponding to at least one of a plurality of items;

generate at least one statistic corresponding to the media content activity; and

generate a taste profile attribute by using the at least one statistic.

2. The system according to claim 1, wherein the at least one statistic is generated by calculating, for each of the plurality of items, a probability that each of the plurality of items are known and the taste profile attribute is generated by calculating an average of the at least one statistic across the plurality of items.

3. The system according to claim 2, wherein the probability is based on any one of, or a combination of, usage data, a mention of one or more of the plurality of items on a webpage, and an external source of popularity data.

4. The system according to claim 1, wherein the at least one statistic is, for each of the plurality of items, a value representing a type of item and the taste profile attribute is a measure of the a stylistic diversity of two or more of the plurality of items that are the same type of item.

5. The system according to claim 1, wherein the processor is further operable to:

generate a plurality of style maps S_a; and

generate an inverted overlap matrix based on the plurality of style maps,

O<sup>−

1</sup>(S₁, S₂ . . . , S_a),

wherein each of the plurality of style maps S_a is based on a value representative of how connected a predetermined taste profile activity is to a corresponding item of the plurality of items.

6. The system according to claim 1, wherein the taste profile attribute (a) is generated according the equation:

7. The system according to claim 1, wherein the processor is further configured to:

calculate a weighted average of an amount representative of a trending popularity across the named collection of items.

8. The system according to claim 1, wherein the statistic is a plurality of scores representative of recency of each of the plurality of items, correspondingly, and the taste profile attribute is generated by calculating an average of the plurality of scores.

9. The system according to claim 1, wherein the at least one statistic is based on an age of each of the plurality of items and is a probability that each of the plurality of items is known, and the taste profile attribute is generated by calculating an average of the probability across each of the plurality of items.

10. A non-transitory computer-readable medium having stored thereon one or more sequences of instructions for causing one or more processors to perform:

accessing a taste profile containing a representation of media content activity corresponding to at least one of a plurality of items;

generating at least one statistic corresponding to the media content activity; and

generating a taste profile attribute by using the at least one statistic.

11. The computer-readable medium of claim 10, wherein the at least one statistic is generated by calculating, for each of the plurality of items, a probability that each of the plurality of items are known and the taste profile attribute is generated by calculating an average of the at least one statistic across the plurality of items.

12. The computer-readable medium of claim 11, wherein the probability is based on any one of, or a combination of, usage data, a mention of one or more of the plurality of items on a webpage, and an external source of popularity data.

13. The computer-readable medium of claim 10, wherein the at least one statistic is, for each of the plurality of items, a value representing a type of item and the taste profile attribute is a measure of the a stylistic diversity of two or more of the plurality of items that are the same type of item.

14. The computer-readable medium of claim 10, wherein the processor is further operable to:

generate a plurality of style maps S_a; and

generate an inverted overlap matrix based on the plurality of style maps,

O<sup>−

1</sup>(S₁, S₂ . . . , S_a),

wherein each of the plurality of style maps S_a is based on a value representative of how connected a predetermined taste profile activity is to a corresponding item of the plurality of items.

15. The computer-readable medium of claim 10, wherein the taste profile attribute (a) is generated according the equation:

16. The computer-readable medium of claim 10, wherein the processor is further configured to:

calculate a weighted average of an amount representative of a trending popularity across the named collection of items.

17. The computer-readable medium of claim 10, wherein the statistic is a plurality of scores representative of recency of each of the plurality of items, correspondingly, and the taste profile attribute is generated by calculating an average of the plurality of scores.

18. The computer-readable medium of claim 10, wherein the at least one statistic is based on an age of each of the plurality of items and is a probability that each of the plurality of items is known, and the taste profile attribute is generated by calculating an average of the probability across each of the plurality of items.

19. A method for summarizing user activity associated with media content, comprising the steps of:

accessing a taste profile containing a representation of media content activity corresponding to at least one of a plurality of items;

generating at least one statistic corresponding to the media content activity; and

generating a taste profile attribute by using the at least one statistic.

20. The method of claim 19, wherein the at least one statistic is generated by calculating, for each of the plurality of items, a probability that each of the plurality of items are known and the taste profile attribute is generated by calculating an average of the at least one statistic across the plurality of items.

21. The method of claim 20, wherein the probability is based on any one of, or a combination of, usage data, a mention of one or more of the plurality of items on a webpage, and an external source of popularity data.

22. The method of claim 19, wherein the at least one statistic is, for each of the plurality of items, a value representing a type of item and the taste profile attribute is a measure of the a stylistic diversity of two or more of the plurality of items that are the same type of item.

23. The method of claim 19, wherein the processor is further operable to:

generate a plurality of style maps S_a; and

generate an inverted overlap matrix based on the plurality of style maps,

O<sup>−

1</sup>(S₁, S₂ . . . , S_a),

wherein each of the plurality of style maps S_a is based on a value representative of how connected a predetermined taste profile activity is to a corresponding item of the plurality of items.

24. The method of claim 19, wherein the taste profile attribute (a) is generated according the equation:

25. The method of claim 19, wherein the processor is further configured to:

calculate a weighted average of an amount representative of a trending popularity across the named collection of items.

26. The method of claim 19, wherein the statistic is a plurality of scores representative of recency of each of the plurality of items, correspondingly, and the taste profile attribute is generated by calculating an average of the plurality of scores.

27. The method of claim 19, wherein the at least one statistic is based on an age of each of the plurality of items and is a probability that each of the plurality of items is known, and the taste profile attribute is generated by calculating an average of the probability across each of the plurality of items.