SYSTEM FOR DETECTING ASSOCIATIONS BETWEEN ITEMS

• US 20090089273A1
• Filed: 09/27/2007
• Published: 04/02/2009
• Est. Priority Date: 09/27/2007
• Status: Active Grant

• Current Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Original Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Inventors: Hicks, Cory
• Granted Patent: US 7,779,040 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/00 Information retrieval; Database structures therefor; File system structures therefor
• CPC Class Codes: G06F 7/00 Methods or arrangements for processing data by operating upon the order or content of the data handled logic circuits H03K19/00
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0631 Item recommendations

Abstract

A method of detecting associations between items can include identifying a plurality of items represented in a data repository from which to select items to recommend to a target user, each item including one or more attributes. A degree of fit between an item'"'"'s attributes and other items is calculated. The degree of fit can indicate the relevance of the attributes of one item to the other item. A degree of association between the two items is calculated based at least in part on the calculated degree of fit. The degree of association between the two items can indicate the relatedness of the two items. Based on this degree of association, an association between the items can be stored in a data repository.

Claims

1. A computer-implemented method of detecting associations between items represented in a data repository, the method comprising:

identifying a plurality of items represented in a data repository from which to select items to recommend to a target user, each item having one or more attributes;

calculating a degree of fit of the attributes of a first item with a second item, the degree of fit reflecting the relevance of the attributes of the first item to the second item, wherein calculating the degree of fit comprises;

forming an initial matrix of values, each of the attributes of the first and second items having a value represented in the initial matrix;

calculating a singular value decomposition of the initial matrix, the singular value decomposition comprising a left matrix, a singular value matrix, and a right transpose matrix;

reducing the dimension of one or more of the left, singular value, and right transpose matrices to create a reduced singular value decomposition; and

multiplying the matrices of the reduced singular value decomposition to create a reduced-dimension matrix approximating the initial matrix;

calculating a correlation value between the values in the reduced-dimension matrix corresponding to the first and second items, the correlation value representing a degree of association between the first and second items, the degree of association between the first and second items reflecting the relatedness of the first and second items; and

programmatically using the calculated correlation value between the first and second items to create, in computer storage, an association between the first and second items.

2. The method of claim 1, wherein the items include at least one of movies, apparel, music, books, and television shows.

3. The method of claim 2, wherein the items comprise movies and the attributes comprise contributors to the movies, the contributors including at least one of actors, directors, producers, narrators, and writers.

4. The method of claim 3, wherein calculating a degree of fit further comprises predicting which actors would likely contribute to a movie with other actors.

5. The method of claim 1, further comprising using the associations to generate recommendations for the target user.

6. A computer-implemented method of detecting associations between items represented in a data repository, the method comprising:

identifying a plurality of items represented in a data repository from which to select items to recommend to a target user, each item comprising one or more attributes;

calculating a degree of fit of the attributes of a first item with a second item, the degree of fit reflecting the relevance of the attributes of the first item to the second item;

calculating a degree of association between the first and second items based at least in part on the calculated degree of fit, the degree of association between the first and second items indicating the relatedness of the first and second items; and

storing the calculated degree of association in computer storage.

7. The method of claim 6, wherein calculating a degree of fit comprises:

forming an initial matrix of values corresponding to the attributes of the first and second items; and

reducing the dimension of the initial matrix to form a reduced-dimension matrix approximating the initial matrix.

8. The method of claim 7, wherein reducing the dimension of the initial matrix comprises using a singular value decomposition of the initial matrix to reduce the dimension of the initial matrix.

9. The method of claim 7, wherein calculating a degree of association between the first and second items based on the calculated degree of fit comprises calculating correlation values between values in the reduced-dimension matrix.

10. The method of claim 6, wherein the items include at least one of movies, apparel, music, books, e-books, television shows, and electronics.

11. The method of claim 10, wherein the items are movies and the attributes comprise contributors to the movies, the contributors including at least one of actors, directors, producers, narrators, writers, and film studios.

12. The method of claim 6, wherein calculating a degree of fit further comprises assigning values to the attributes based at least in part on attribute type.

13. The method of claim 11, wherein calculating a degree of fit further comprises assigning values to the attributes based at least in part on popularity of the contributors.

14. A computer system for detecting associations between items represented in a data repository, the system comprising:

an item attributes analysis component configured to;

identify a plurality of items represented in a data repository from which to select items to recommend to a target user, each item comprising one or more attributes;

calculate a degree of fit of the attributes of a first item with a second item, the degree of fit reflecting the relevance of the attributes of the first item to the second item; and

an association analysis component configured to;

calculate a degree of association between the first and second items based at least in part on the calculated degree of fit, the degree of association between the first and second items indicating the relatedness of the first and second items; and

store the calculated degree of association in computer storage.

15. The apparatus of claim 14, wherein the item attributes analysis component calculates a degree of fit by:

forming an initial matrix of values corresponding to the attributes of the first and second items; and

reducing the dimension of the initial matrix to form a reduced-dimension matrix approximating the initial matrix.

16. The apparatus of claim 15, wherein the item attributes analysis component is further configured to assign values to the attributes based at least in part on attribute type.

17. A computer-implemented method of detecting associations between media contributors, the method comprising:

identifying a plurality of media contributors each associated with one or more works represented in a data repository;

calculating a degree of fit of one or more works of a first contributor with a second contributor, the degree of fit indicating the relevance of the one or more works of the first contributor to the second contributor;

calculating a degree of association between the first and second contributors based at least in part on the calculated degree of fit, the degree of association between the first and second contributors reflecting the relatedness of the first and second contributors; and

storing a result of the calculated degree of association in computer storage.

18. The method of claim 17, wherein the works comprise at least one of the following:

movies, television shows, music, and books.

19. The method of claim 17, wherein the contributors comprise at least one of the following:

actors, authors, musicians, directors, producers, narrators, and writers.

20. The method of claim 17, wherein calculating a degree of fit comprises:

forming an initial matrix of values corresponding to the attributes of the first and second items; and

reducing the dimension of the initial matrix to form a reduced-dimension matrix approximating the initial matrix.

21. The method of claim 17, wherein calculating a degree of fit further comprises assigning values to the contributors based at least in part on contributor type.

22. The method of claim 17, wherein calculating a degree of fit further comprises assigning values to the contributors based at least in part on customer reviews of the contributors.

23. A computer-implemented method of assessing a degree of association between a first work having a first contributor and a second work having a second contributor, the method comprising:

calculating a first degree of association between the first contributor and the second work;

calculating a second degree of association between the second contributor and the first work; and

assessing a degree of association between the first and second works based, at least in part, on the first and second calculated degrees of association.

24. The method of claim 23, wherein the first and second works are movies and the contributors comprise at least one of actors, directors, producers, narrators, writers, and film studios.

25. The method of claim 24, wherein calculating a first degree of association comprises applying latent semantic analysis techniques to the first contributor and the second work.

26. The method of claim 23, wherein the first contributor is not a contributor of the second work and wherein the second contributor is not a contributor of the first work.

27. A computer-implemented method of detecting associations between works, the method comprising:

identifying a first work having a first contributor;

identifying a second work having a second contributor, the second contributor not being a contributor to the first work, and the first contributor not being a contributor to the second work; and

calculating a degree of association between the first work and the second work based, at least in part, on an extent to which the first and second contributors co-contribute to one or more other works.

28. The method of claim 27, wherein the first and second works are movies and the first and second contributors are actors in the movies.

29. The method of claim 27, wherein the works comprise musical works.

30. The method of claim 27, wherein calculating the degree of association comprises taking into consideration acting roles of the first and second contributors in said one or more other works.