EXTRAPOLATION OF ITEM ATTRIBUTES BASED ON DETECTED ASSOCIATIONS BETWEEN THE ITEMS

• US 20100299360A1
• Filed: 07/13/2010
• Published: 11/25/2010
• Est. Priority Date: 06/16/2006
• Status: Abandoned Application

• Current Assignee: Jin Y. Yi
• Original Assignee: Jin Y. Yi
• Inventors: Yi, Jin Y.
• Application Number:
  US12/835,125
• Publication Number:
  US 20100299360A1
• Time in Patent Office: Days
• US Class Current: 707/776
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0601 Electronic shopping [e-shopping]
• CPC Class Codes: G06Q 30/0629 for generating comparisons
• CPC Class Codes: G06Q 30/0631 Item recommendations

Abstract

An attribute of a first item is extrapolated to a second item that is not known to have that attribute. The extrapolation occurs as a result of a substitution association detected between the first and second items. The substitution association may be detected based on an analysis of the content of the first and second items. The extrapolated attribute may be a behavioral association with a third item, in which case an inference is drawn that the second and third items are behaviorally related. The items may, for example, be products represented in an electronic catalog.

Claims

1. A computer system for detecting associations between items, the computer system comprising:

an item data repository comprising a physical computer storage device, the item data repository configured to store item data representative of a plurality of items, the plurality of items comprising first items having an attribute and second items not known to have the attribute;

a content-based association mining component operative to detect substitution associations between the first and second items, at least in part, by analyzing content of the first and second items; and

an extrapolation component that comprises computer hardware, the extrapolation component operative to extrapolate the attribute from at least some of the first items to the second items based at least partly on a strength of the substitution associations between the first and second items.

2. The computer system of claim 1, wherein the extrapolation component is further configured to extrapolate the attribute by propagating the attribute through a directed graph, the directed graph comprising nodes, each node representing a selected one of the plurality of items.

3. The computer system of claim 1, wherein the extrapolation component is further configured to propagate the attribute through the directed graph based at least partly on strength of associations between the plurality of items.

4. The computer system of claim 1, wherein the attribute is a behavioral association.

5. The computer system of claim 1, further comprising a recommendations module operative to generate item recommendations for a user based at least in part on the attribute.

6. The computer system of claim 5, wherein the recommendations module is further operative to use the attribute to improve recommendations for behavior-deficient items.

7. The computer system of claim 5, wherein the content-based association mining component comprises computer hardware.

8. The computer system of claim 5, wherein the items are products represented in an electronic catalog, and the content-based association mining component uses catalog content of said products to detect said substitution associations.

9. A computer-implemented method, comprising:

identifying a first item that has a first attribute, and a second item that is not known to have said first attribute;

determining a strength of a substitution association between the first and second items based, said strength determined based on least partly on an automated analysis of content of the first and second items; and

extrapolating the first attribute to the second item based on said strength of said substitution association;

said method performed in its entirety by one or more computers.

10. The method of claim 9, wherein extrapolating the first attribute comprises propagating the first attribute according to a directed graph that comprises a plurality of nodes, each node representing an item.

11. The method of claim 9, wherein the first attribute is a behavioral association with a third item.

12. The method of claim 9, further comprising treating the second item as having said first attribute for purposes of automatically determining whether to recommend the second to a user.

13. The method of claim 9, wherein the first and second items are products represented in an electronic catalog, and the method comprises determining said strength based on an automated analysis of catalog content of the first and second items.