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A computer-implemented service associated with an electronic catalog analyzes purchase histories of users, and/or other types of activity data reflective of user affinities for specific items, to identify items that are significantly more popular in specific user communities than in a general user p

A computer-implemented service associated with an electronic catalog analyzes purchase histories of users, and/or other types of activity data reflective of user affinities for specific items, 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), shipping address based communities (e.g., all users with shipping addresses in Seattle), and/or communities based on other types of user attributes. In one embodiment, a user of the service can select a particular community, such as by selecting the name of a corresponding organization or geographic region, to view a list of items having relatively high popularity levels therein. The results of the analysis may additionally or alternatively be used to affirmatively notify users of associations between particular items and communities, and/or to recommend items to users.

대표청구항 ▼

What is claimed is: 1. A computer system having one or more processors, the computer system comprising: an electronic data repository that stores user activity data associated with each of a plurality of users, said user activity data reflecting user affinities for particular items represented in a

What is claimed is: 1. A computer system having one or more processors, the computer system comprising: an electronic data repository that stores user activity data associated with each of a plurality of users, said user activity data reflecting user affinities for particular items represented in an electronic catalog, said electronic data repository comprising a computer memory; a first component that analyzes the user activity data of the plurality of users, in conjunction with data that associates particular users with particular user communities, to identify, for each of a plurality of said user communities, a respective set of items that are significantly more popular in the respective user community than in a general user population; and a second component that provides electronic user access to information that associates the sets of items with the corresponding user communities to assist users in selecting items from the electronic catalog. 2. The computer system of claim 1, wherein the first component identifies a set of items that are significantly more popular in a given user community, at least in part, by comparing item activity levels associated with the given user community to corresponding item activity levels associated with the general user population. 3. The computer system of claim 1, wherein the first component uses a bootstrap method to evaluate whether a set of items associated with a particular user community is a result of group preferences that differ from preferences of the general user population. 4. The computer system of claim 1, wherein the user activity data analyzed by the first component identifies items purchased by specific users. 5. The computer system of claim 1, wherein the user activity data analyzed by the first component identifies items rented by specific users. 6. The computer system of claim 1, wherein the user activity data analyzed by the first component is reflective of item ratings submitted by users. 7. The computer system of claim 1, wherein the user activity data analyzed by the first component reflects click-though events to item detail pages of the electronic catalog. 8. The computer system of claim 1, wherein the user communities include email-address-based user communities. 9. The computer system of claim 1, wherein the user communities include communities associated with particular organizations, and wherein the first component treats a user as being affiliated with one of said organizations if an email address of the user contains a string associated with the organization. 10. The computer system of claim 1, wherein the user communities include shipping-address-based user communities. 11. The computer system of claim 1, wherein the user communities include explicit-membership communities that users explicitly join via a user interface of the computer system. 12. The computer system of claim 1, wherein the second component is an interactive component that is responsive to user selection of a particular user community by outputting a list of the set of items corresponding to the particular user community. 13. The computer system of claim 1, wherein the second component is a notification component that generates email-based notifications of items that are popular in particular user communities. 14. The computer system of claim 1, wherein the second component uses information about the sets of items identified by the first component, in combination with data that associates a target user with a particular user community, to select items to recommend to the target user. 15. The computer system of claim 1, wherein the items include physical products that are shipped to users. 16. The computer system of claim 1, wherein the items include movie titles rented by users. 17. The computer system of claim 1, wherein the first component identifies said set of items for a particular user community based on the user activity data of both members and non-members of the particular user community. 18. The computer system of claim 1, wherein the first component identifies said set of items for a particular user community using an algorithm that identifies items that distinguish the particular user community from the general user population. 19. The computer system of claim 1, wherein the second component is operative to generate, for presentation to a user, a display page that includes a name of a particular user community and a list of items that are significantly more popular in the particular user community than in the general user population. 20. The computer system of claim 1, further comprising at least one physical server that executes said first component. 21. The computer system of claim 1, wherein said second component comprises a web server that provides interactive user access to said information. 22. The computer system of claim 1, wherein the computer system additionally includes a component that provides functionality for the users to communicate with each other regarding particular catalog items represented in the electronic catalog. 23. The computer system of claim 1, wherein the computer system additionally includes a component that enables a first user who is interested in a particular catalog item to identify, and initiate communications with, a second user who has purchased the particular catalog item. 24. A computer-implemented method performed by a computer system that includes one or more physical computers, the method comprising: storing, in an electronic data repository, user activity data associated with each of a plurality of users, said user activity data reflecting user affinities for particular items represented in an electronic catalog, said electronic data repository comprising a computer memory; via execution of a first component, analyzing the user activity data of the plurality of users, in conjunction with data that associates particular users with particular user communities, to identify, for each of a plurality of said user communities, a respective set of items that are significantly more popular in the respective user community than in a general user population; and via execution of a second component, providing electronic user access to information that associates the sets of items with the corresponding user communities to assist users in selecting items from the electronic catalog. 25. The method of claim 24, wherein the first component identifies a set of items that are significantly more popular in a given user community, at least in part, by comparing item activity levels associated with the given user community to corresponding item activity levels associated with the general user population. 26. The method of claim 24, wherein the first component uses a bootstrap method to evaluate whether a set of items associated with a particular user community is a result of group preferences that differ from preferences of the general user population. 27. The method of claim 24, wherein the user activity data identifies items purchased by specific users. 28. The method of claim 24, wherein the user activity data identifies items rented by specific users. 29. The method of claim 24, wherein the user activity data analyzed by the first component includes item ratings submitted by users. 30. The method of claim 24, wherein the user activity data reflects click-though events to item detail pages of the electronic catalog. 31. The method of claim 24, wherein the user communities include email-address-based user communities. 32. The method of claim 24, wherein the user communities include communities associated with particular organizations, and wherein the first component treats a user as being affiliated with one of said organizations when an email address of the user contains a domain associated with the organization. 33. The method of claim 24, wherein the user communities include shipping-address-based user communities. 34. The method of claim 24, wherein the user communities include explicit-membership communities that users explicitly join via a user interface of the computer system. 35. The method of claim 24, further comprising, via execution of said second component, responding to user selection of a particular user community by outputting a list of the set of items corresponding to the particular user community. 36. The method of claim 24, further comprising, via execution of said second component, generating email-based notifications containing said information that associates the sets of items with the corresponding user communities. 37. The method of claim 24, wherein the second component uses information about the sets of items identified via execution of the first component, in combination with data that associates a target user with a particular user community, to select items to recommend to the target user. 38. The method of claim 24, wherein the items include physical products that are shipped to users. 39. The method of claim 24, wherein the items include movie titles rented by users. 40. The method of claim 24, wherein the first component identifies said set of items for a particular user community based on the user activity data of both members and non-members of the particular user community. 41. The method of claim 24, wherein the first component identifies said set of items for a particular user community using an algorithm that identifies items that distinguish the particular user community from the general user population. 42. The method of claim 24, wherein the second component generates, for presentation to a user, a display page that includes a name of a particular user community and a list of items that are significantly more popular in the particular user community than in the general user population. 43. The method of claim 24, wherein said electronic user access is provided by a server. 44. The method of claim 24, wherein the analysis of the user activity data is performed by at least one server that executes the first component. 45. The method of claim 24, further comprising, via said computer system, providing a service that enables the users to communicate with each other regarding particular items represented in the electronic catalog.