Recommender system for identifying a new set of media items responsive to an input set of media items and knowledge base metrics

• US 9,262,534 B2
• Filed: 11/12/2012
• Issued: 02/16/2016
• Est. Priority Date: 02/03/2005
• Status: Expired due to Fees

• Current Assignee: Apple Inc.
• Original Assignee: Apple Inc.
• Inventors: Martin, Francisco J., Shur, Jim, Torrens, Marc
• Primary Examiner(s): ALAM, SHAHID AL
• Application Number:
  US13/674,820
• Publication Number:
  US 20130080455A1
• Time in Patent Office: 1,191 Days
• Field of Search: 707/722, 707/736, 707/737, 707/754, 707/780, 707/916, 707/948
• US Class Current: 1/1
• CPC Class Codes: G06F 16/435 Filtering based on additional data, e.g. user or group profiles
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0631 Item recommendations
• CPC Class Codes: H04N 21/466 Learning process for intelligent management, e.g. learning user preferences for recommending movies services using the results of monitoring in broadcast systems H04H60/61
• CPC Class Codes: H04N 21/4668 for recommending content, e.g. movies
• CPC Class Codes: H04N 21/4825 using a list of items to be played back in a given order, e.g. playlists
• CPC Class Codes: H04N 7/163 by receiver means only

Abstract

Systems and methods are disclosed for identifying a new set of media items in response to an input set (or “query set”) of media items and knowledge base metrics. The system uses a knowledge base consisting of a collection of mediasets. Various metrics among media items are considered by analyzing how the media items are grouped to form the mediasets in the knowledge base. Such association or “similarity” metrics are preferably stored in a matrix form that allows the system to efficiently identify a new set of media items that complements the input set of media items.

Claims

1. A method comprising:

storing, in a memory location, a plurality of media sets for a community of users; and

preprocessing, using a processor, the plurality of media sets to quantify an association between pairs of media items, comprising;

for each item in a mediaset, identifying every other item in the same mediaset, so as to define all of the pairs of media items in that mediaset;

repeating said identifying step for every other mediaset in the plurality of media sets, thereby defining every pair of items that appears in any mediaset in the plurality of media sets;

for each identified pair of media items, adjusting a concurrency metric value responsive to each additional occurrence of the same pair of items in the plurality of media sets;

storing media library collection data for a plurality of user accounts;

receiving, from a client device, information about at least one input media item;

identifying a candidate set of media items by selecting media having an adjusted concurrency value over a predetermined threshold value and containing the at least one input media item;

accessing the user account associated with the client device; and

filtering the candidate set based on the media library collection data for the user of the client device.

2. The method of claim 1, wherein the concurrency metric value is a co-concurrency metric value, and adjusting comprises incrementing the co-concurrency metric value responsive to every additional occurrence of the same pair of items in the plurality of media sets.

3. The method of claim 1, wherein:

the media items are ordered within the mediasets in the plurality of media sets;

identifying comprises defining ordered pairs of items that appear in any mediaset in the plurality of media sets in the same order;

the concurrency metric value is an ordered concurrency metric value, and adjusting comprises incrementing the ordered concurrency metric value responsive to every additional occurrence of the same ordered pair of items in the plurality of media sets.

4. The method of claim 1, further comprising:

selecting one or more of the ordered pairs by evaluating the metric value.

5. The method of claim 4, further comprising:

sending a recommendation output set of media items to the client device, the output set comprising media items paired with the at least one input media item.

6. The method of claim 5, further comprising:

receiving, along with the input media item, one or more recommendation preferences from the client device relating to what types of media items a user prefers to receive in the recommendation output set of media items; and

filtering the output set according to the one or more recommendation preferences.

7. The method of claim 5, further comprising:

filtering the output set based on metadata of the at least one input media item.

8. The method of claim 1, further comprising:

sending a recommendation output set of media items to the client device, the output set comprising a filtered candidate set.

9. A system for preprocessing a knowledge base for sending media recommendations comprising:

a database for storing a plurality of media sets for a community of users; and

a processor for preprocessmg the plurality of media sets to quantify an association between pairs of media items, wherein the processor is further configured to;

for each item in a mediaset, identify every other item in the same mediaset, so as to define all of the pairs of media items in that mediaset;

repeat said identifying step for every other mediaset in the plurality of media sets, thereby defining every pair of items that appears in any mediaset in the plurality of media sets;

for each identified pair of media items, adjust a concurrency metric value responsive to each additional occurrence of the same pair of items in the plurality of media sets;

store media library collection data for a plurality of user accounts;

receive, from a client device, information about at least one input media item;

identify a candidate set of media items by selecting media having an adjusted concurrency value over a predetermined threshold value and containing the at least one input media item;

access the user account associated with the client device; and

filter the candidate set based on the media library collection data for the user of the client device.

10. The system of claim 9, wherein the concurrency metric value is a co-concurrency metric value, and wherein the processor is further configured increment the co-concurrency metric value responsive to every additional occurrence of the same pair of items in the plurality of media sets.

11. The system of claim 9, wherein the media items are ordered within the mediasets in the plurality of media sets, wherein the processor is configured to define ordered pairs of items that appear in any mediaset in the plurality of media sets in the same order, wherein the concurrency metric value is an ordered concurrency metric value, and wherein the processor is further configured to increment the ordered concurrency metric value responsive to every additional occurrence of the same ordered pair of items in the plurality of media sets.

12. The system of claim 9, wherein the processor is further configured to:

select one or more of the ordered pairs by evaluating the metric value.

13. The system of claim 12, wherein the processor is further configured to:

send a recommendation output set of media items to the client device, the output set comprising media items paired with the at least one input media item.

14. The system of claim 13, wherein the processor is further configured to:

receive, along with the input media item, one or more recommendation preferences from the client device relating to what types of media items a user prefers to receive in the recommendation output set of media items; and

filter the output set according to the one or more recommendation preferences.

15. The system of claim 13, wherein the processor is further configured to:

filter the output set based on metadata of the at least one input media item.

16. A non-transitory computer-readable medium comprising:

a medium configured to store computer-readable instructions thereon; and

the computer-readable instructions that, when executed by a processing device cause the processing device to perform a method, comprising;

storing a plurality of media sets for a community of users; and

preprocessing the plurality of media sets to quantify an association between pairs of media items in the plurality of media sets, comprising;

for each item in a mediaset, identifying every other item in the same mediaset, so as to define all of the pairs of media items in that mediaset;

repeating said identifying step for every other mediaset in the plurality of media sets, thereby defining every pair of items that appears in any mediaset in the plurality of media sets;

for each identified pair of media items, adjusting a concurrency metric value responsive to each additional occurrence of the same pair of items in the plurality of media sets;

storing media library collection data for a plurality of user accounts;

receiving, from a client device, information about at least one input media item;

identifying a candidate set of media items by selecting media having an adjusted concurrency value over a predetermined threshold value and containing the at least one input media item;

accessing the user account associated with the client device; and

filtering the candidate set based on the media library collection data for the user of the client device.

17. The non-transitory computer-readable storage medium of claim 16, wherein the concurrency metric value is a co-concurrency metric value, and adjusting comprises incrementing the co-concurrency metric value responsive to every additional occurrence of the same pair of items in the plurality of media sets.

18. The non-transitory computer-readable storage medium of claim 16, wherein the media items are ordered within the mediasets in the plurality of media sets, the instructions further comprising identifying comprises defining ordered pairs of items that appear in any mediaset in the plurality of media sets in the same order, and wherein the concurrency metric value is an ordered concurrency metric value, and adjusting comprises incrementing the ordered concurrency metric value responsive to every additional occurrence of the same ordered pair of items in the plurality of media sets.

19. The non-transitory computer-readable storage medium of claim 16, the instructions further comprising:

selecting one or more of the ordered pairs by evaluating the metric value.

20. The non-transitory computer-readable storage medium of claim 16, the instructions further comprising:

sending a recommendation output set of media items to the client device, the output set comprising media items paired with the at least one input media item.

21. The non-transitory computer-readable storage medium of claim 20, the instructions further comprising:

receiving, along with the input media item, one or more recommendation preferences from the client device relating to what types of media items a user prefers to receive in the recommendation output set of media items; and

filtering the output set according to the one or more recommendation preferences.

22. The non-transitory computer-readable storage medium of claim 20, the instructions further comprising:

filtering the output set based on metadata of the at least one input media item.

23. The non-transitory computer-readable storage medium of claim 20, the instructions further comprising:

storing media library collection data for a plurality of user accounts in relation to the knowledge base;

upon receiving the input media item, accessing the user account associated with the client device; and

filtering the output set based on the user of the client device'"'"'s media library.

24. A method comprising:

storing a plurality of mediasets for a community of users;

defining every pair of media items that appear together in any media set of the plurality of mediasets;

for each defined pair of media items, assigning a concurrency value to the defined pair, the concurrency value representing the number of times the defined pair appears in a mediaset;

storing media library collection data for a plurality of user accounts in relation to the plurality of mediasets;

receiving, from a client device, information about at least one input media item;

identifying a candidate set of media items by selecting media having the concurrency value over a predetermined threshold value and containing the at least one input media item;

accessing the user account associated with the client device; and

filtering the candidate set based on the media library collection data for the user of the client device.

25. The method of claim 24, wherein the concurrency value is a co-concurrency metric value.

26. The method of claim 24, wherein the media items are ordered within the mediasets in the plurality of media sets, further comprising:

selecting one or more of the ordered pairs by evaluating the metric value.

27. The method of claim 24, further comprising:

sending a recommendation output set of media items to the client device, the output set comprising media items paired with the at least one input media item.

28. The method of claim 24, further comprising:

receiving, along with the input media item, one or more recommendation preferences from the client device relating to what types of media items a user prefers to receive in the recommendation output set of media items; and

filtering the output set according to the one or more recommendation preferences.

29. The method of claim 24, further comprising:

filtering the output set based on metadata of the at least one input media item.

30. The method of claim 24, further comprising:

sending a recommendation output set of media items to the client device, the output set comprising a filtered candidate set.