IDENTIFYING AND ROUTING OF DOCUMENTS OF POTENTIAL INTEREST TO SUBSCRIBERS USING INTEREST DETERMINATION RULES

• US 20100299140A1
• Filed: 05/20/2010
• Published: 11/25/2010
• Est. Priority Date: 05/22/2009
• Status: Abandoned Application

• Current Assignee: Cycorp, Inc.
• Original Assignee: Cycorp, Inc.
• Inventors: Shepard, Kevin Blake, Mladenic, Dunja, Fortuna, Blaz, Grobelnik, Marko, Lefkowitz, Lawrence Seth, Schneider, David Andrew, Witbrock, Michael John
• Application Number:
  US12/783,675
• Publication Number:
  US 20100299140A1
• Time in Patent Office: Days
• US Class Current: 704/9
• CPC Class Codes: G06Q 10/10 Office automation; Time management

Abstract

A method, system and computer program product for identifying documents of interest. A profile of a subscriber is created based on information obtained about the subscriber. Subscriber-interest determination rules are used to identify potential topics of interest of the subscriber based on the subscriber'"'"'s profile as well as based on external knowledge sources. Each potential interest of the subscriber may be represented by a pointer that references a concept. Additionally, concepts in the documents published by the publishers are identified. A comparison may be made between the concepts identified in the documents published by the publishers with those concepts representing the potential topics of interests of the subscriber. Those documents with matching concepts may then be identified as potentially being of interest for the subscriber. In this manner, documents of interest are more accurately identified for the document seeker.

Claims

1. A method for identifying documents of interest, the method comprising:

identifying potential topics of interests of a subscriber based on a profile of said subscriber and knowledge sources using subscriber-interest determination rules, wherein said potential topics of interests are represented as pointers to concepts;

identifying concepts contained in each of a plurality of documents;

associating each identified concept with that document;

comparing said identified concepts in said plurality of documents with said concepts representing said potential topics of interests of said subscriber; and

identifying one or more documents in said plurality of documents whose concepts match with said concepts representing said potential topics of interests of said subscriber.

2. The method as recited in claim 1 further comprising:

acquiring information about said subscriber; and

creating said profile of said subscriber based on said acquired information about said subscriber.

3. The method as recited in claim 1 further comprising:

notifying said subscriber of said identified one or more documents.

4. The method as recited in claim 3, wherein said notification comprises one or more of the following:

one or more titles of said identified one or more documents, one or more pointers to said identified one or more documents, one or more rationales for selecting said identified one or more documents, and full text of said identified one or more documents.

5. The method as recited in claim 3 further comprising:

receiving a request from said subscriber to retrieve one or more of said identified one or more documents.

6. The method as recited in claim 5 further comprising:

providing said requested one or more of said identified one or more documents to said subscriber.

7. The method as recited in claim 1 further comprising:

receiving feedback from said subscriber regarding a quality of said identification of one or more documents in said plurality of documents whose concepts match with said concepts representing said potential topics of interests of said subscriber.

8. The method as recited in claim 7 further comprising:

modifying said subscriber-interest determination rules in response to said feedback from said subscriber.

9. The method as recited in claim 7 further comprising:

modifying which concepts are to be identified in each of said plurality of documents in response to said feedback from said subscriber.

10. The method as recited in claim 1 further comprising:

generating assertions by applying said subscriber-interest determination rules to said profile of said subscriber and to said knowledge sources, wherein said assertions are stored in a model.

11. The method as recited in claim 10, wherein said assertions are assigned to one or more categories.

12. The method as recited in claim 10, wherein said assertions are stored in said model using predicate calculus.

13. The method as recited claim 1, wherein each of said concepts representing said potential topics of interests of said subscriber has a unique identifier.

14. The method as recited in claim 1, wherein said identified potential topics of interests of said subscriber are represented in a structured fashion.

15. The method as recited in claim 1 further comprising:

deriving a rationale for identifying a potential topic of interest using said subscriber-interest determination rules.

16. The method as recited in claim 1, wherein said identified potential topics of interests of said subscriber and associated rationales for said identified potential topics of interests of said subscriber based on said subscriber-interest determination rules are represented in a structured fashion.

17. A computer program product embodied in a computer readable storage medium for identifying documents of interest, the computer program product comprising the programming instructions for:

identifying potential topics of interests of a subscriber based on a profile of said subscriber and knowledge sources using subscriber-interest determination rules, wherein said potential topics of interests are represented as pointers to concepts;

identifying concepts contained in each of a plurality of documents;

associating each identified concept with that document;

comparing said identified concepts in said plurality of documents with said concepts representing said potential topics of interests of said subscriber; and

identifying one or more documents in said plurality of documents whose concepts match with said concepts representing said potential topics of interests of said subscriber.

18. The computer program product as recited in claim 17 further comprising the programming instructions for:

acquiring information about said subscriber; and

creating said profile of said subscriber based on said acquired information about said subscriber.

19. The computer program product as recited in claim 17 further comprising the programming instructions for:

notifying said subscriber of said identified one or more documents.

20. The computer program product as recited in claim 19, wherein said notification comprises one or more of the following:

one or more titles of said identified one or more documents, one or more pointers to said identified one or more documents, one or more rationales for selecting said identified one or more documents, and full text of said identified one or more documents.

21. The computer program product as recited in claim 19 further comprising the programming instructions for:

receiving a request from said subscriber to retrieve one or more of said identified one or more documents.

22. The computer program product as recited in claim 21 further comprising the programming instructions for:

providing said requested one or more of said identified one or more documents to said subscriber.

23. The computer program product as recited in claim 17 further comprising the programming instructions for:

receiving feedback from said subscriber regarding a quality of said identification of one or more documents in said plurality of documents whose concepts match with said concepts representing said potential topics of interests of said subscriber.

24. The computer program product as recited in claim 23 further comprising the programming instructions for:

modifying said subscriber-interest determination rules in response to said feedback from said subscriber.

25. The computer program product as recited in claim 23 further comprising the programming instructions for:

modifying which concepts are to be identified in each of said plurality of documents in response to said feedback from said subscriber.

26. The computer program product as recited in claim 17 further comprising the programming instructions for:

generating assertions by applying said subscriber-interest determination rules to said profile of said subscriber and to said knowledge sources, wherein said assertions are stored in a model.

27. The computer program product as recited in claim 26, wherein said assertions are assigned to one or more categories.

28. The computer program product as recited in claim 26, wherein said assertions are stored in said model using predicate calculus.

29. The computer program product as recited claim 17, wherein each of said concepts representing said potential topics of interests of said subscriber has a unique identifier.

30. The computer program product as recited in claim 17, wherein said identified potential topics of interests of said subscriber are represented in a structured fashion.

31. The computer program product as recited in claim 17 further comprising the programming instructions for:

deriving a rationale for identifying a potential topic of interest using said subscriber-interest determination rules.

32. The computer program product as recited in claim 17, wherein said identified potential topics of interests of said subscriber and associated rationales for said identified potential topics of interests of said subscriber based on said subscriber-interest determination rules are represented in a structured fashion.

33. A system, comprising:

a memory unit for storing a computer program for identifying documents of interest; and

a processor coupled to said memory unit, wherein said processor, responsive to said computer program, comprises;

circuitry for identifying potential topics of interests of a subscriber based on a profile of said subscriber and knowledge sources using subscriber-interest determination rules, wherein said potential topics of interests are represented as pointers to concepts;

circuitry for identifying concepts contained in each of a plurality of documents;

circuitry for associating each identified concept with that document;

circuitry for comparing said identified concepts in said plurality of documents with said concepts representing said potential topics of interests of said subscriber; and

circuitry for identifying one or more documents in said plurality of documents whose concepts match with said concepts representing said potential topics of interests of said subscriber.

34. The system as recited in claim 33, wherein said processor further comprises:

circuitry for acquiring information about said subscriber; and

circuitry for creating said profile of said subscriber based on said acquired information about said subscriber.

35. The system as recited in claim 33, wherein said processor further comprises:

circuitry for notifying said subscriber of said identified one or more documents.

36. The system as recited in claim 35, wherein said notification comprises one or more of the following:

one or more titles of said identified one or more documents, one or more pointers to said identified one or more documents, one or more rationales for selecting said identified one or more documents, and full text of said identified one or more documents.

37. The system as recited in claim 35, wherein said processor further comprises:

circuitry for receiving a request from said subscriber to retrieve one or more of said identified one or more documents.

38. The system as recited in claim 37, wherein said processor further comprises:

circuitry for providing said requested one or more of said identified one or more documents to said subscriber.

39. The system as recited in claim 33, wherein said processor further comprises:

circuitry for receiving feedback from said subscriber regarding a quality of said identification of one or more documents in said plurality of documents whose concepts match with said concepts representing said potential topics of interests of said subscriber.

40. The system as recited in claim 39, wherein said processor further comprises:

circuitry for modifying said subscriber-interest determination rules in response to said feedback from said subscriber.

41. The system as recited in claim 39, wherein said processor further comprises:

circuitry for modifying which concepts are to be identified in each of said plurality of documents in response to said feedback from said subscriber.

42. The system as recited in claim 33, wherein said processor further comprises:

circuitry for generating assertions by applying said subscriber-interest determination rules to said profile of said subscriber and to said knowledge sources, wherein said assertions are stored in a model.

43. The system as recited in claim 42, wherein said assertions are assigned to one or more categories.

44. The system as recited in claim 42, wherein said assertions are stored in said model using predicate calculus.

45. The system as recited claim 33, wherein each of said concepts representing said potential topics of interests of said subscriber has a unique identifier.

46. The system as recited in claim 33, wherein said identified potential topics of interests of said subscriber are represented in a structured fashion.

47. The system as recited in claim 33, wherein said processor further comprises:

circuitry for deriving a rationale for identifying a potential topic of interest using said subscriber-interest determination rules.

48. The system as recited in claim 33, wherein said identified potential topics of interests of said subscriber and associated rationales for said identified potential topics of interests of said subscriber based on said subscriber-interest determination rules are represented in a structured fashion.