Identifying associations between items and email-address-based user communities

• US 7,970,660 B2
• Filed: 07/09/2009
• Issued: 06/28/2011
• Est. Priority Date: 04/09/1999
• Status: Expired due to Fees

• Current Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Original Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Inventors: McAuliffe, Jon, Spiegel, Joel R., Bezos, Jeffrey P.
• Primary Examiner(s): ZURITA, JAMES H
• Application Number:
  US12/500,507
• Publication Number:
  US 20090281877A1
• Time in Patent Office: 719 Days
• Field of Search: 705/26.1, 705/27.1
• US Class Current: 705/26.1
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0254 based on statistics
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions
• CPC Class Codes: G06Q 30/0601 Electronic shopping [e-shopping]
• CPC Class Codes: G06Q 30/0613 Third-party assisted
• CPC Class Codes: G06Q 30/0623 Item investigation
• 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: G06Q 30/0645 Rental transactions; Leasing transactions
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

A computer-implemented service analyzes collected data reflective of actions of users of an interactive system to identify items that are significantly more popular in specific user communities than in a general user population. The communities may, for example, include email-based communities (e.g., all users with email addresses associated with a particular company or other organization), shipping address based communities (e.g., all users with shipping addresses in Seattle), and/or communities based on other types of user attributes. The results of the analysis may be exposed to users to assist users in making item selection decisions, and/or may be used to provide item recommendations to users.

Claims

1. A computer-implemented data mining method, comprising:

storing, in an electronic data repository, user activity data associated with each of a plurality of users of an online system that provides access to an electronic catalog, said user activity data reflecting user-generated events associated with particular items represented in the electronic catalog;

programmatically identifying, among the plurality of users, a subset of users whose email addresses are associated with a particular organization;

programmatically analyzing the user activity data associated with the plurality of users, including the subset of users, by execution of code by a computer processor, to identify a set of items that have experienced significantly higher levels of user activity among the subset of users than among the plurality of users; and

creating, in computer storage, an association between the organization and the identified set of items.

2. The method of claim 1, further comprising electronically exposing to users of the electronic catalog the association between the organization and the set of items.

3. The method of claim 2, wherein electronically exposing the association comprises providing access, via a web site that hosts the electronic catalog, to a web page that lists the set of items and a name of the organization.

4. The method of claim 2, wherein electronically exposing the association comprises transmitting, to an email address of a user, a notification message that associates the organization with one or more items in said set.

5. The method of claim 2, wherein the organization is a company.

6. The method of claim 1, further comprising, based on said association, electronically recommending items in said set to at least some of the users in said subset of users.

7. The method of claim 1, further comprising using the association to generate personalized item recommendations for users.

8. The method of claim 1, wherein programmatically analyzing the user activity data comprises comparing item popularity levels associated with the subset of users to corresponding item popularity levels associated with the plurality of users.

9. The method of claim 1, wherein programmatically analyzing the user activity data comprises using a bootstrap method to evaluate whether a set of items associated with the organization is a result of group preferences that differ from preferences of the plurality of users.

10. The method of claim 1, wherein programmatically analyzing the user activity data comprises applying an algorithm that identifies items that distinguish the subset of users from users whose email addresses do not reveal an association with the organization.

11. The method of claim 1, wherein the user-generated events comprise item purchase events.

12. The method of claim 1, wherein the user-generated events comprise item rental events.

13. The method of claim 1, wherein the user-generated events include at least one of the following:

(a) user submissions of item ratings, (b) shopping cart add events, (c) click-through events to item detail pages.

14. The method of claim 1, wherein the items include physical products that are shipped to users.

15. The method of claim 1, wherein the items include movie titles rented by users.

16. A computer system comprising one or more computers, said computer system programmed, via executable code stored in computer storage, to perform a method that comprises:

storing, in an electronic data repository, user activity data associated with each of a plurality of users of an interactive system that provides access to an electronic catalog, said user activity data reflecting user-generated events associated with particular items represented in the electronic catalog;

identifying, among the plurality of users, a subset of users whose email addresses are associated with a particular organization;

analyzing the user activity data associated with the plurality of users, including the subset of users, to identify, among the items represented in the electronic catalog, a set of items that have experienced significantly higher levels of user activity among the subset of users than among the plurality of users; and

storing, in computer storage, association data that associates the organization with the identified set of items.

17. The computer system of claim 16, wherein the computer system is further programmed to use the association data to cause an association between the organization and the identified set of items to be exposed to users of the interactive system.

18. The computer system of claim 17, wherein the computer system is programmed to cause said association to be exposed by generating, for presentation to a user, a document that lists the set of items and a name of the organization.

19. The computer system of claim 18, wherein the organization is a company.

20. The computer system of claim 16, wherein the computer system is further programmed to use the association data to cause items in said set to be recommended to at least some of the users in said subset of users.

21. The computer system of claim 16, wherein analyzing the user activity data comprises comparing item popularity levels associated with the subset of users to corresponding item popularity levels associated with the plurality of users.

22. The computer system of claim 16, wherein analyzing the user activity data comprises using a bootstrap method to evaluate whether a set of items associated with the organization is a result of group preferences that differ from preferences of the plurality of users.

23. The computer system of claim 16, wherein analyzing the user activity data comprises applying an algorithm that identifies items that distinguish the subset of users from users whose email addresses do not reveal an association with the organization.

24. The computer system of claim 16, wherein the user-generated events comprise item purchase events.

25. The computer system of claim 16, wherein the user-generated events comprise item rental events.

26. Physical computer storage that stores executable code that instructs a computer system to perform a method that comprises:

storing user activity data associated with each of a plurality of users of an interactive system that provides access to a data repository of information regarding items, said user activity data reflecting user-generated events associated with particular items represented in said data repository;

identifying, among the plurality of users, a subset of users whose email addresses are associated with a particular organization;

analyzing the user activity data associated with the plurality of users, including the subset of users, to identify, among said items represented in the data repository, a set of items that have experienced significantly higher levels of user activity among the subset of users than among the plurality of users; and

storing, in computer storage, association data that associates the organization with the identified set of items.

27. The physical computer storage of claim 26, wherein the executable code additionally directs the computer system to use said association data to expose, to users of the interactive system, an association between the organization and items in said set.

28. The physical computer storage of claim 26, wherein the executable code additionally directs the computer system to use said association data to provide recommendations of items to users.

29. The physical computer storage of claim 26, wherein the items are catalog items represented in an electronic catalog.

30. The physical computer storage of claim 26, wherein the organization is a company.

31. The physical computer storage of claim 26, wherein analyzing the user activity data comprises applying an algorithm that identifies items that distinguish the subset of users from users whose email addresses do not reveal an association with the organization.