DISCOVERY OF BEHAVIOR-BASED ITEM RELATIONSHIPS

• US 20110238525A1
• Filed: 06/06/2011
• Published: 09/29/2011
• Est. Priority Date: 09/18/1998
• Status: Active Grant

• Current Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Original Assignee: Brent R. Smith, Gregory D. Linden, Nida K. Zada
• Inventors: Smith, Brent R., Linden, Gregory D., Zada, Nida K.
• Granted Patent: US 8,407,105 B2
• Time in Patent Office: Days
• US Class Current: 705/26.7
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0253 During e-commerce, i.e. online transactions
• CPC Class Codes: G06Q 30/0254 based on statistics
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: G06Q 30/0256 User search
• CPC Class Codes: G06Q 30/0271 Personalized advertisement
• CPC Class Codes: G06Q 30/0277 Online advertisement
• CPC Class Codes: G06Q 30/0282 Rating or review of business operators or products
• CPC Class Codes: G06Q 30/0601 Electronic shopping [e-shopping]
• CPC Class Codes: G06Q 30/0603 Catalogue ordering
• CPC Class Codes: G06Q 30/0631 Item recommendations
• CPC Class Codes: G06Q 30/0633 Lists, e.g. purchase orders, compilation or processing
• CPC Class Codes: G06Q 30/0641 Shopping interfaces
• CPC Class Codes: H04L 51/02 using automatic reactions or user delegation, e.g. automatic replies or chatbot-generated messages
• CPC Class Codes: Y10S 707/99943 Generating database or data structure, e.g. via user interface

Abstract

Various processes are disclosed for discovering item relationships between particular items, such as products represented in an electronic catalog, based on monitored user behaviors (e.g., item viewing activities, item purchases, shopping cart activities, etc.). The discovered item relationships may, for example, be used to generate personalized item recommendations for users, and/or to supplement item detail pages of an electronic catalog with lists of related items. Also disclosed are processes for generating personalized item recommendations based on users'"'"' search activities and browse node visits.

Claims

1. A computer-implemented method of discovering behavior-based relationships between items represented in an electronic catalog, the method comprising:

storing a plurality of session records in computer storage, each session record being specific to a respective browsing session of a user and identifying a plurality of items selected by the user for viewing in an electronic catalog during the browsing session, at least some of said session records corresponding to different users than other browsing records;

generating data values representing strengths of relationships between particular ones of said items, wherein generating the data values comprises, for a pair of items, determining, based on the plurality of session records, the number of browsing sessions in which both items of the pair were selected for viewing; and

generating a mapping of items to related items based at least partly on said data values;

said method performed by a computing system that comprises one or more computers.

2. The method of claim 1, wherein generating the data values comprises treating user accesses to item detail pages of the electronic catalog as selections of corresponding items for viewing.

3. The method of claim 2, further comprising using said mapping to supplement item detail pages of the electronic catalog with lists of related items.

4. The method of claim 1, further comprising causing an item detail page for a first item to be supplemented with a list of additional items and with an indication that the additional items are viewed by users who view the first item, said list based on said mapping.

5. The method of claim 1, further comprising using the mapping, in combination with a record of a plurality of items selected by a user during a current browsing session, to select items to recommend to the user during the current browsing session.

6. The method of claim 1, wherein generating the data values comprises determining, for said pair of items, the number of browsing sessions in which only one of the two items of the pair was selected for viewing.

7. The method of claim 1, wherein generating the data values comprises using item purchase histories of users as an additional measure of item relatedness.

8. The method of claim 1, further comprising generating said session records based on monitored browsing activity of users such that each session record corresponds to a respective period of substantially continuous browsing activity.

9. The method of claim 1, further comprising generating said session records based on monitored browsing activity of users, wherein generating said session records comprises determining whether a particular browsing session has ended based at least partly on whether a checkout transaction has occurred.

10. The method of claim 1, wherein at least some of the session records are stored as anonymous session records that are not linked to corresponding users.

11. A system for discovering behavior-based relationships between items represented in an electronic catalog, the system comprising:

a computer data repository that stores a plurality of session records, each session record being specific to a respective browsing session of a user and identifying a plurality of items selected by the user for viewing in an electronic catalog during the browsing session, at least some of said session records corresponding to different users than other browsing records; and

a computing system programmed to at least;

generate data values representing strengths of relationships between particular ones of said items using a method that comprises determining, based on the plurality of session records, the number of sessions in which both items of the pair were selected for viewing; and

generate a mapping of items to related items based at least partly on said data values.

12. The system of claim 11, wherein the system, in generating the data values, is configured to treat each user access to an item detail page of the electronic catalog as a selection of a corresponding item for viewing.

13. The system of claim 12, further comprising a component that is configured to use said mapping to supplement item detail pages of the electronic catalog with corresponding lists of related items.

14. The system of claim 11, further comprising a component that is configured to supplement an item detail page for a first item with a list of additional items, and with an indication that the additional items are viewed by users who view the first item, said list based on the mapping.

15. The system of claim 11, further comprising a recommendation system configured to use the mapping, in combination with a record of a plurality of items selected by a user for viewing during a current browsing session, to select items to recommend to the user during the current browsing session.

16. The system of claim 11, wherein the method additionally comprises determining, for the pair of items, the number of browsing sessions in which only one of the two items of the pair was selected for viewing.

17. The system of claim 11, further comprising a component that is configured to generate said session records based on monitored browsing activity of users such that each session record corresponds to a respective period of substantially continuous browsing activity.

18. The system of claim 11, further comprising a component that is configured to generate the session records based on monitored browsing activity of users, said component configured to determine whether a particular browsing session has ended based at least partly on whether a checkout transaction has occurred.

19. The system of claim 11, wherein at least some of the session records are stored in said data repository as anonymous session records.

20. A system for discovering and exposing behavior-based relationships between items represented in an electronic catalog, the system comprising:

a computer data repository that stores records of item viewing activities of a plurality of users, said records of item viewing activities identifying particular items selected by users for viewing in an electronic catalog of items;

a first component that is configured to generate a mapping of items to related items based on the records of item viewing activities, said mapping reflecting item-viewing-based relationships between items, said first component comprising computer hardware; and

a second component that is configured to use the mapping to incorporate lists of related items into item detail pages of the electronic catalog.

21. The system of claim 20, wherein the second component is configured to supplement an item detail page for a first item with a list of additional items, and with an indication that the additional items are viewed by users who view the first item, said list based on said mapping.

22. The system of claim 20, wherein the first component is configured to analyze the item viewing activities on a session-by-session basis to identify items that tend to be viewed during the same browsing session.

23. The system of claim 20, wherein the items are products capable of being purchased via the electronic catalog.

24. The system of claim 20, wherein the records of item viewing activities are based on visits to item detail pages of the electronic catalog.

25. A method of discovering item relationships, the method comprising:

storing, in computer storage, records of electronic shopping cart contents of each of a plurality of users of an interactive system that provides electronic shopping carts, said records of shopping cart contents identifying particular items selected by users to add to their electronic shopping carts; and

generating, based at least partly on the records of electronic shopping cart contents, a mapping that maps items to corresponding sets of related items;

said method performed by a computing system that comprises one or more computers.

26. The method of claim 25, wherein generating said mapping comprises generating data values for specific item pairs, each data value representing a degree of relationship between a first item and a second item and being dependent upon how frequently both the first item and the second item are added to a common electronic shopping cart.

27. The method of claim 26, wherein generating the data values comprises counting a number times that both the first item and the second item were concurrently in a common electronic shopping cart.

28. The method of claim 26, wherein generating the data values comprises counting a number of sessions in which both the first item and the second item were added to a common electronic shopping cart.

29. The method of claim 25, further comprising using the mapping to generate personalized item recommendations for each of a plurality of users.

30. The method of claim 29, wherein using the mapping to generate personalized item recommendations for each of a plurality of users comprises replicating the mapping across a plurality of physical servers that are configured with executable code for using the mapping to generate personalized item recommendations.

31. A system for discovering item relationships, the system comprising:

a computer data repository that contains records of electronic shopping cart contents associated with each of a plurality of users of an interactive system that provides electronic shopping carts, said records of shopping cart contents identifying particular items selected by users to add to their electronic shopping carts; and

a computing system programmed to generate, based at least partly on the records of electronic shopping cart contents, a mapping that maps specific items to sets of related items.

32. The system of claim 31, wherein the computing system is programmed to generate data values for specific item pairs, each data value representing a degree of relationship between two items of a respective item pair and being dependent upon how many times the two items have co-occurred in an electronic shopping cart.

33. The system of claim 32, wherein the computing system is programmed to generate the data values using a method that comprises, for an item pair consisting of a first item and a second item, counting a number of times that both the first item and the second item were concurrently in a common electronic shopping cart.

34. The system of claim 32, wherein the computing system is programmed to generate the data values using a method that comprises, for an item pair consisting of a first item and a second item, counting a number of sessions in which both the first item and the second item were added to a common electronic shopping cart.

35. The system of claim 31, further comprising a recommendation system configured to use the mapping to generate personalized item recommendations for users.

36. The system of claim 35, wherein the recommendation system comprises a plurality of physical servers, each of which stores a copy of said mapping and stores executable code for using the mapping to generate personalized item recommendations.