Personalized product recommendation

• US 20030208399A1
• Filed: 05/03/2002
• Published: 11/06/2003
• Est. Priority Date: 05/03/2002
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Krishnapuram, Raghuram, Basak, Jayanta
• Application Number:
  US10/138,857
• Publication Number:
  US 20030208399A1
• Time in Patent Office: Days
• US Class Current: 705/14
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: G06Q 30/0271 Personalized advertisement

Abstract

A method, system and computer program product for generating a personalized list of items for a user are disclosed. The method includes the steps of storing inter-item relationships, adaptively identifying and storing users'"'"' interests based on behavioral patterns of users and generating a personalized list of items for a user, based on the user'"'"'s stored interests and the inter-item relationships. The method optionally includes the additional steps of identifying and storing attributes of items and defining the inter-item relationships on the basis of the degree of similarity between item attributes. A user'"'"'s interests can also be categorized on the basis of item attributes. The system and computer program product disclosed are for performing the steps of the foregoing method.

Claims

1. A method for generating a personalized item list for a user, said method including the steps of:

storing inter-item relationships;

adaptively identifying and storing users'"'"' interests based on behavioral patterns of said users; and

generating a personalized list of items for a user, based on said user'"'"'s stored interests and said inter-item relationships.

2. The method of claim 1, including the further steps of:

identifying and storing attributes of a plurality of items; and

defining inter-item relationships based on the degree of similarity between attributes of said items.

3. The method of claim 2, including the further step of categorizing said user'"'"'s interests based on said attributes of said items.

4. The method of claim 3, wherein said users'"'"' interests are stored in a structure selected from the group consisting of:

a tree-like structure; and

a digraph-like structure.

5. The method of claim 2, wherein said step of defining inter-item relationships is further based on a requirement to promote certain items.

6. The method of claim 2, wherein said step of defining inter-relationships is further based on historical interest in items by users.

7. A method according to claim 1 for personalized media mining, wherein said items comprise World Wide Web pages and said personalized list of items comprises a personalized list of World Wide Web pages.

8. A method according to claim 1 for content-based image retrieval and similarity search, wherein said items comprise images and said personalized list of items comprises a personalized list of images.

9. A method according to claim 1 for distance education and digital library search, wherein said items comprise educational material and said personalized list of items comprises a personalized list of educational material.

10. A method according to claim 1 for targeted advertising, wherein said inter-item relationships comprise item-advertisment relationships and said personalized list of items comprises a list of advertisments.

11. A method according to claim 1 for targeting potential customers, wherein said items comprise potential customers and said personalized list of items comprises a list of potential customers to be targeted.

12. A system for generating a personalized item list for a user, including:

means for storing inter-item relationships;

means for adaptively identifying and storing users'"'"' interests based on behavioral patterns of said users; and

means for generating a personalized list of items for a user, based on said user'"'"'s stored interests and said inter-item relationships.

13. The system of claim 12, further including:

means for identifying and storing attributes of a plurality of items; and

means for defining inter-item relationships based on the degree of similarity between attributes of said items.

14. The system of claim 13, further including means for categorizing said user'"'"'s interests based on said attributes of said items.

15. The system of claim 14, wherein said users'"'"' interests are stored in a structure selected from the group consisting of:

a tree-like structure; and

a digraph-like structure.

16. The system of claim 13, wherein definition of said inter-item relationships is further based on a requirement to promote certain items.

17. The system of claim 13, wherein definition of said inter-item relationships is further based on a history interest in items by users.

18. A system according to claim 12 for personalized media mining, wherein said items comprise World Wide Web pages and said personalized list of items comprises a personalized list of World Wide Web pages.

19. A system according to claim 12 for content-based image retrieval and similarity search, wherein said items comprise images and said personalized list of items comprises a personalized list of images.

20. A system according to claim 12 for distance education and digital library search, wherein said items comprise educational material and said personalized list of items comprises a personalized list of educational material.

21. A system according to claim 12 for targeted advertising, wherein said inter-item relationships comprise item-advertisment relationships and said personalized list of items comprises a list of advertisments.

22. A system according to claim 12 for targeting potential customers, wherein said items comprise potential customers and said personalized list of items comprises a list of potential customers to be targeted.

23. A computer program product comprising a computer readable medium having a computer program recorded therein for generating a personalized item list for a user, said computer program product including:

computer program code means for storing inter-item relationships;

computer program code means for adaptively identifying and storing users'"'"' interests based on behavioral patterns of said users; and

computer program code means for generating a personalized list of items for a user, based on said user'"'"'s stored interests and said inter-item relationships.

24. The computer program product of claim 23, further including:

computer program code means for identifying and storing attributes of a plurality of items; and

computer program code means for defining inter-item relationships based on the degree of similarity between attributes of said items.

25. The computer program product of claim 24, further including computer program code means for categorizing said user'"'"'s interests based on said attributes of said items.

26. The computer program product of claim 25, wherein said users'"'"' interests are stored in a structure selected from the group consisting of:

a tree-like structure; and

a digraph-like structure.

27. The computer program product of claim 24, wherein definition of said inter-item relationships is further based on a requirement to promote certain items.

28. The computer program product of claim 24, wherein definition of said inter-item relationships is further based on historical interest in items by users.

29. A computer program product according to claim 23 for personalized media mining, wherein said items comprise World Wide Web pages and said personalized list of items comprises a personalized list of World Wide Web pages.

30. A computer program product according to claim 23 for content-based image retrieval and similarity search, wherein said items comprise images and said personalized list of items comprises a personalized list of images.

31. A computer program product according to claim 23 for distance education and digital library search, wherein said items comprise educational material and said personalized list of items comprises a personalized list of educational material.

32. A computer program product according to claim 23 for targeted advertising, wherein said inter-item relationships comprise item-advertisment relationships and said personalized list of items comprises a list of advertisments.

33. A computer program product according to claim 23 for targeting potential customers, wherein said items comprise potential customers and said personalized list of items comprises a list of potential customers to be targeted.