Relevancy association architecture

• US 20070043717A1
• Filed: 08/18/2005
• Published: 02/22/2007
• Est. Priority Date: 08/18/2005
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Halliday-Reynolds, Elizabeth, Burton, Mary, Read, Jason, Yakesch, Douglas, Arellanes, Paul, Liu, William
• Application Number:
  US11/207,056
• Publication Number:
  US 20070043717A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/3331 Query processing
• CPC Class Codes: G06F 16/9558 Details of hyperlinks; Management of linked annotations

Abstract

A relevancy association architecture for providing a more effective retrieval of existing product support information in response to client information requests. Product support information for products of a business enterprise is collected and stored in an information library. Relevancy associations are created, based on an ontology such as a context-scenario information organization model, among the product support information stored in the information library and the products provided by the business enterprise. Once the relevancy associations are created, weights are assigned to the associations, wherein the weights designate the certainty of each created relevancy association. When a client requests support for a product of the business enterprise, relevant product support information for the client request is identified based on the relevancy associations. This relevant product support information may then be sent to the requesting client.

Claims

1. A computer implemented method for organizing product support information in a business enterprise, the computer implemented method comprising:

collecting product support information for products provided by the business enterprise;

storing the product support information in an information library as information objects;

creating relevancy associations among the information objects stored in the information library and the products provided by the business enterprise, wherein the relevancy associations are created based on an ontology; and

assigning relevancy weights to the relevancy associations, wherein the relevancy weights designate a certainty of each relevancy association.

2. The computer implemented method of claim 1, further comprising:

receiving a product support request from a client;

identifying relevant information objects in the information library for the product support request based on the relevancy associations; and

sending relevant product support information associated with the identified information objects to the client.

3. The computer implemented method of claim 2, wherein the step of identifying relevant information objects includes determining an information object is relevant if the information object has a relevancy weight greater than or equal to a relevancy threshold in the relevancy criteria.

4. The computer implemented method of claim 1, wherein the ontology is a context-scenario information organization model, and wherein context in the context-scenario information organization model identifies circumstances in which the product support information is needed, and wherein scenario in the context-scenario information organization model identifies events occurring within the context that cause a need for the product support information.

5. The computer implemented method of claim 1, wherein the step of creating relevancy associations further comprises:

associating an information object in the information library to a product provided by the business enterprise.

6. The computer implemented method of claim 1, wherein the step of creating relevancy associations further comprises:

propagating a relevancy association for a node combination to a nearby node combination based on the ontology.

7. The computer implemented method of claim 1, wherein a positive weight is assigned to a relevancy association to identify relevant information objects, and a negative weight is assigned to a relevancy association to identify irrelevant information objects.

8. The computer implemented method of claim 1, wherein relevancy association weights are assigned based on a user type that created the relevancy associations.

9. The computer implemented method of claim 1, wherein the product support information is collected from sources internal to the business enterprise.

10. The computer implemented method of claim 2, wherein the relevant product support information sent to the client comprises product support information at a business solution level.

11. The computer implemented method of claim 1, wherein each information object in the information library has one or more relevancy associations.

12. A relevancy association apparatus comprising:

an interface, wherein the interface receives product support information;

an information library, wherein the information library stores the product support information received by the interface; and

a relevancy module, wherein the relevancy module creates relevancy associations among the information objects stored in the information library and the products provided by the business enterprise, wherein the relevancy associations are created based on an ontology, and assigns relevancy weights to the relevancy associations, wherein the relevancy weights designate a certainty of each relevancy association.

13. The data processing system of claim 12, wherein the interface receives a product support request from a client and the relevancy module identifies relevant information objects in the information library for the product support request based on the relevancy associations, wherein product support information associated with the identified relevant information objects is sent to the client.

14. The relevancy association apparatus of claim 12, wherein the interface comprises an aggregation interface which receives product support information from aggregation sources.

15. A computer program product for organizing product support information in a business enterprise, the computer program product comprising:

a computer usable medium having computer usable program code tangibly embodied thereon, the computer usable program code comprising;

computer usable program code for collecting product support information for products provided by the business enterprise;

computer usable program code for storing the product support information in an information library as information objects;

computer usable program code for creating relevancy associations among the information objects stored in the information library and the products provided by the business enterprise, wherein the relevancy associations are created based on an ontology; and

computer usable program code for assigning relevancy weights to the relevancy associations, wherein the relevancy weights designate a certainty of each relevancy association.

16. The computer program product of claim 15, further comprising:

computer usable program code for receiving a product support request from a client;

computer usable program code for identifying relevant information objects in the information library for the request based on the relevancy associations; and

computer usable program code for sending relevant product support information associated with the identified information objects to the client.

17. The computer program product of claim 16, wherein the computer usable program code for identifying relevant information objects further comprises code for determining that an information object is relevant if the information object has a relevancy weight greater than or equal to a relevancy threshold in the relevancy criteria.

18. The computer program product of claim 15, wherein the computer usable program code for creating relevancy associations further comprises code for propagating a relevancy association for a node combination to a nearby node combination based on the ontology.

19. The computer program product of claim 15, wherein a positive weight is assigned to a relevancy association to identify relevant information objects, and a negative weight is assigned to a relevancy association to identify irrelevant information objects.

20. The computer program product of claim 15, wherein relevancy association weights are assigned based on a user type that created the relevancy associations.