System and method for scoring messages within a system for harvesting community kowledge

• US 20040024719A1
• Filed: 07/31/2002
• Published: 02/05/2004
• Est. Priority Date: 07/31/2002
• Status: Abandoned Application

• Current Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Original Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Inventors: Lukose, Rajan Mathew, Adar, Eytan, Sengupta, Caesar, Tyler, Joshua Rogers
• Application Number:
  US10/210,593
• Publication Number:
  US 20040024719A1
• Time in Patent Office: Days
• US Class Current: 706/12
• CPC Class Codes: G06N 5/00 Computing arrangements using knowledge-based models

Abstract

A system and method for scoring messages within a privacy-preserving knowledge management is disclosed. The method of the present invention discloses, generating a message including a set of data items within a message field; transmitting the message from a sending client to a set of receiving clients; generating a receiving client profile on one of the receiving clients; extracting the data items from the profile; and scoring the data items in the message with respect to the data items in the profile. Alternatively the method can include, generating a receiving client profile on at a receiving client; storing the profile on the computer; receiving a message including a set of data items within a message field; extracting the data items from the profile; and scoring the data items in the message with respect to the data items in the profile. The system of the present invention, discloses means for implementing the method.

Claims

1. A method for knowledge management, comprising:

generating a message including a set of data items within a message field;

transmitting the message from a sending client to a set of receiving clients;

generating a receiving client profile on one of the receiving clients;

extracting the data items from the profile; and

scoring the data items in the message with respect to the data items in the profile.

2. The method of claim 1 wherein the set of data items are keywords.

3. The method of claim 1 wherein the set of data items are key-phrases.

4. The method of claim 1 wherein the set of data items are structured data items.

5. The method of claim 1 wherein the set of data items are unstructured data items.

6. The method of claim 1 wherein the scoring element further including:

generating a first expertise vector for a data item in the message;

generating a second expertise vector for a data item in the profile; and

comparing the first and second expertise vectors.

7. The method of claim 6 wherein generating the first and second expertise vector elements include generating the first and second expertise vectors using information retrieval techniques.

8. The method of claim 1 wherein the scoring element further including:

generating a first expertise vector magnitude equal to a relative term frequency of the data item in the message;

generating a first expertise vector magnitude equal to a relative term frequency of the data item in the profile; and

comparing the first and second expertise vector magnitudes.

9. The method of claim 1 wherein

the generating a receiving client profile element includes indexing data targets within the profile;

and

the scoring element includes totaling the number of indexed data targets containing at least one occurrence of the data item.

10. The method of claim 1 wherein the generating a message element includes generating a message, having a set of filtering criteria.

11. The method of claim 10 wherein the generating a message element further includes including a structured data item into the filtering criteria.

12. The method of claim 10 wherein the generating a message element further includes including an unstructured data item into the filtering criteria.

13. The method of claim 10 wherein the generating a message element further includes including a behavioral data item into the filtering criteria.

14. The method of claim 10 wherein the generating a message element further includes requiring that a data item within the filtering criteria be found within a self-declared portion of the profile.

15. The method of claim 10 wherein the generating a message element further includes requiring that a data item within the filtering criteria be found within a URL portion of the profile.

16. The method of claim 10 wherein the generating a message element further includes requiring that a data item within the filtering criteria be found within an installed software portion of the profile.

17. The method of claim 10 wherein the generating a message element further includes requiring that a data item within the filtering criteria be found within an e-mail address portion of the profile.

18. The method of claim 10 wherein the scoring element further includes

assigning a first filter score to a filtering criteria within the set, if that filtering criteria within the set is found within the profile;

and

assigning a second filter score to that filtering criteria within the set, if that filtering criteria is not found within the profile.

19. The method of claim 8 wherein the scoring element further includes:

assigning a first filter score to a filtering criteria within the set, if that filtering criteria within the set is found within the profile;

assigning a second filter score to that filtering criteria within the set, if that filtering criteria is not found within the profile; and

calculating an overall score from the expertise vectors and the filter scores.

20. The method of claim 19, wherein:

the generating element includes generating a message including a set of hierarchical rules for calculating the overall score; and

the calculating element includes calculating the overall score according to the hierarchical rules.

21. The method of claim 19, wherein:

the generating element includes generating a message including a set of logical rules for calculating the overall score; and

the calculating element includes calculating the overall score according to the logical rules.

22. A method for knowledge management, comprising:

generating a receiving client profile on at a receiving client;

storing the profile on the computer;

receiving a message including a set of data items within a message field;

extracting the data items from the profile; and

scoring the data items in the message with respect to the data items in the profile.

23. The method of claim 22 wherein the scoring element further including:

generating a first expertise vector for a data item in the message;

generating a second expertise vector for a data item in the profile; and

comparing the first and second expertise vectors.

24. The method of claim 23 wherein

the generating a message element includes generating a message, having a set of filtering criteria;

and

the scoring element further includes,

assigning a first filter score to a filtering criteria within the set, if that filtering criteria within the set is found within the profile;

assigning a second filter score to that filtering criteria within the set, if that filtering criteria is not found within the profile; and

calculating an overall score from the expertise vectors and the filter scores.

25. A system for knowledge management, comprising:

means for generating a message including a set of data items within a message field;

means for transmitting the message from a sending client to a set of receiving clients;

means for generating a receiving client profile on one of the receiving clients;

means for extracting the data items from the profile; and

means for scoring the data items in the message with respect to the data items in the profile.

26. A system for knowledge management, comprising:

means for generating a receiving client profile on at a receiving client;

means for storing the profile on the computer;

means for receiving a message including a set of data items within a message field;

means for extracting the data items from the profile; and

means for scoring the data items in the message with respect to the data items in the profile.