Mining of user event data to identify users with common interests

• US 9,792,332 B2
• Filed: 12/12/2016
• Issued: 10/17/2017
• Est. Priority Date: 03/30/2005
• Status: Expired due to Fees

• Current Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Original Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Inventors: Spiegel, Joel R.
• Primary Examiner(s): Arjomandi, Noosha
• Application Number:
  US15/376,111
• Publication Number:
  US 20170091194A1
• Time in Patent Office: 309 Days
• CPC Class Codes: G06F 16/24 Querying
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/2465 Query processing support for facilitating data mining operations in structured databases
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/08 Auctions
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: H04L 12/1813 for computer conferences, e.g. chat rooms instant messaging H04L51/04; protocols for multimedia communication H04L65/1101; arrangements for multi-party communication H04L65/403; telephonic conference arrangements H04M3/56; television conference systems H04N7/15
• CPC Class Codes: H04L 51/52 for supporting social networking services
• CPC Class Codes: H04L 67/306 User profiles

Abstract

A computer-implemented matching service matches users to other users, and/or to user communities, based at least in part on a computer analysis of event data reflective of user behaviors. The event data may, for example, evidence user affinities for particular items represented in an electronic catalog, such as book titles, music titles, movie titles, and/or other types of items that tend to reflect the traits of users. Event data reflective of other types of user actions, such as item-detail-page viewing events, browse node visits, search query submissions, and/or web browsing patterns may additionally or alternatively be considered. By taking such event data into consideration, the matching service reduces the burden on users to explicitly supply personal profile information, and reduces poor results caused by exaggerations and other inaccuracies in such profile information.

Claims

1. A computer-implemented method comprising:

storing, in computer storage, event data representing user-generated events that reflect user affinities for particular items, wherein the user-generated events comprise user actions that can be monitored by a computing device;

generating a score that reflects a degree to which item affinities of a first user of a plurality of users are similar to item affinities of a second user of said plurality of users, said score taking into consideration a first plurality of user-generated events by the first user reflecting a set of item affinities of the first user, and a second plurality of user-generated events by the second user reflecting a set of item affinities of the second user, wherein generating the score further comprises accessing item similarity data to determine whether an item in the set of item affinities of the first user is similar to an item in the set of item affinities of the second user; and

based at least in part on the score, determining whether to output to the first user information about the second user.

2. The method of claim 1, wherein the user-generated events exclude entry of data into a profile.

3. The method of claim 2, wherein said score further takes into consideration profile data.

4. The method of claim 1, wherein the score reflects a degree to which an item in the set of item affinities of the first user is related to an item in the set of item affinities of the second user.

5. The method of claim 1, wherein the information output to the first user includes about item affinities of the second user.

6. The method of claim 1, wherein generating the score comprises:

identifying items of a first type in common between the set of item affinities of the first and second users;

identifying items of a second, different type in common between the set of item affinities of the first and second users; and

weighting each of the identified common items as a function of the respective type of the identified common item.

7. The method of claim 1, wherein said score further takes into consideration at least one additional type of event data reflective of user affinities for items.

8. The method of claim 1, wherein the at least one additional type of event data includes data descriptive of at least one of the following events:

(a) an addition of an item to an electronic shopping cart, (b) an addition of an item to an electronic rental queue, (c) a selection of an item for viewing, (d) a submission of a rating of an item, (e) a selection of an item category in a browse structure, or (f) a submission of a search query to search the electronic catalog.

9. A system comprising:

memory for storing event data representing user-generated events that reflect user affinities for particular items, wherein the user-generated events comprise user actions that can be monitored by a computing device; and

at least one computing device including a processor in communication with the memory, the at least one computing device operative to;

generate a score that reflects a degree to which item affinities of a first user of a plurality of users are similar to item affinities of a second user of said plurality of users, said score taking into consideration a first plurality of user-generated events by the first user reflecting a set of item affinities of the first user, and a second plurality of user-generated events by the second user reflecting a set of item affinities of the second user, wherein generating the score further comprises accessing item similarity data to determine whether an item in the set of item affinities of the first user is similar to an item in the set of item affinities of the second user; and

based at least in part on the score, determine whether to output to the first user information about the second user.

10. The system of claim 9, wherein the user-generated events exclude entry of data into a profile.

11. The system of claim 10, wherein said score further takes into consideration profile data.

12. The system of claim 9, wherein the score reflects a degree to which an item in the set of item affinities of the first user is related to an item in the set of item affinities of the second user.

13. The system of claim 9, wherein the information output to the first user includes about item affinities of the second user.

14. The system of claim 9, wherein generating the score comprises:

identifying items of a first type in common between the set of item affinities of the first and second users;

identifying items of a second, different type in common between the set of item affinities of the first and second users; and

weighting each of the identified common items as a function of the respective type of the identified common item.

15. The system of claim 9, wherein said score further takes into consideration at least one additional type of event data reflective of user affinities for items.

16. The system of claim 15, wherein the at least one additional type of event data includes data descriptive of at least one of the following events:

(a) an addition of an item to an electronic shopping cart, (b) an addition of an item to an electronic rental queue, (c) a selection of an item for viewing, (d) a submission of a rating of an item, (e) a selection of an item category in a browse structure, or (f) a submission of a search query to search the electronic catalog.

17. A computer-implemented method comprising:

storing, in computer storage, event data representing user-generated events that reflect user affinities for particular items, wherein the user-generated events comprise user actions that can be monitored by a computing device;

generating a score that reflects a degree to which item affinities of a first user of a plurality of users are similar to item affinities of a second user of said plurality of users, wherein generating the score further comprises accessing item similarity data to determine whether an item in the set of item affinities of the first user is similar to an item in the set of item affinities of the second user; and

based at least in part on the score, determining whether to output to the first user information about the second user.

18. The method of claim 17, wherein the user-generated events exclude entry of data into a profile.

19. A system comprising:

memory for storing event data representing user-generated events that reflect user affinities for particular items, wherein the user-generated events comprise user actions that can be monitored by a computing device; and

at least one computing device including a processor in communication with the memory, the at least one computing device operative to;

generate a score that reflects a degree to which item affinities of a first user of a plurality of users are similar to item affinities of a second user of said plurality of users, wherein generating the score further comprises accessing item similarity data to determine whether an item in the set of item affinities of the first user is similar to an item in the set of item affinities of the second user; and

based at least in part on the score, determine whether to output to the first user information about the second user.

20. The system of claim 19, wherein the user-generated events exclude entry of data into a profile.