The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Dec. 06, 2011

Filed:

Jan. 27, 2011
Applicants:

Francis J. Kane, Jr., Sammamish, WA (US);

Brent R. Smith, Redmond, WA (US);

Jocelyn M. Miller, Seattle, WA (US);

Shenbagakumaran Srinivasan, Issaquah, WA (US);

Matthew T. Tavis, Seattle, WA (US);

Inventors:

Francis J. Kane, Jr., Sammamish, WA (US);

Brent R. Smith, Redmond, WA (US);

Jocelyn M. Miller, Seattle, WA (US);

ShenbagaKumaran Srinivasan, Issaquah, WA (US);

Matthew T. Tavis, Seattle, WA (US);

Assignee:

Amazon Technologies, Inc., Reno, NV (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06Q 30/00 (2006.01);
U.S. Cl.
CPC ...
Abstract

A service is disclosed for enabling web sites and other entities to provide item recommendations and other behavior-based content to end users. The service can be implemented as a web service that is remotely accessible over the Internet. Web sites use the web service's interface to report events descriptive of item-related actions performed by end users (e.g., item views, item purchases, searches for items, etc.). The web service analyzes the reported event data on an aggregated basis to detect various types of associations between particular items, and stores resulting datasets that map items to associated items. The web service's interface also provides various API calls for enabling the web sites to request item recommendations and other behavior-based content, including but not limited to personalized recommendations that are based on the event history of the target user.


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