SYSTEM AND METHOD OF IDENTIFYING SUBJECT MATTER EXPERTS

• US 20070168345A1
• Filed: 01/17/2007
• Published: 07/19/2007
• Est. Priority Date: 01/17/2006
• Status: Abandoned Application

• Current Assignee: Pantros IP Holding AG
• Original Assignee: Pantros IP Holding AG
• Inventors: Gibbs, Andrew, Gibbs, Stephanie
• Application Number:
  US11/624,051
• Publication Number:
  US 20070168345A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/3344 using natural language analysis
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 50/10 Services

Abstract

A method and system for searching a data collection to identify employee candidates using the text of job description as a semantic search query upon a database containing patent literature or non-patent literature. An exemplary embodiment discloses employee candidates for the described job in a relevancy-ranked order based on the proximity of the search results to the latent semantic analysis search query.

Claims

1. A system for identifying subject matter experts, comprising:

at least one first database populated by at least one first data collection having a plurality of bibliographic text data;

at least one second database that is a semantic database populated by a plurality of pseudo-vectors for expressing a plurality of semantic concepts of the at least one first data collection; and

a search module having at least one search parameter, the search module operatively interfaced with the at least one first database and the at least one second database, whereby the search module is configured to perform on a semantic search query and configured to return at least one relevancy-ranked search result set having at least one candidate.

2. The system of claim 1, wherein the at least one first data collection is at least one patent literature data collection.

3. The system of claim 1, wherein the semantic search query is a textual description of a job opportunity.

4. The system of claim 1, wherein the at least one relevancy-ranked search result set is configured to be sortable.

5. The system of claim 1, further comprising:

at least one inference filter applied to the at least one relevancy-ranked search result set returned by the search module for extracting at least one qualification data for the at least one candidate.

6. The system of claim 5, wherein the at least one inference filter is at least one of a years of experience inference, a knowledge inventory inference, an employment stability inference, a team player characterization inference and a management readiness inference.

7. The system of claim 1, further comprising:

a salary database populated by a plurality of pay scale data responsive to a salary parameter of the search module for use in determining at least one pay scale data for the at least one candidate.

8. The system of claim 1, further comprising:

a location database populated by a plurality of location data responsive to a location parameter of the search module for use in determining at least one relative location data for the at least one candidate.

9. The system of claim 1, further comprising:

a display module configured to display at least one relevancy-ranked search result set.

10. The system of claim 9, wherein the display module is a web browser.

11. A method of identifying subject matter experts, comprising:

submitting a search query to at least one semantic database populated by a plurality of pseudo-vectors expressing a plurality of concepts from at least one data collection populated by a plurality of data;

applying the search query to the at least one semantic database; and

returning at least one result set from the at least one data collection, the result set having at least one subject matter expert candidate data in relevancy-ranked order.

12. The method of claim 11, further comprising:

displaying the at least one result set via a web browser.

13. The method of claim 11, further comprising:

extracting at least one data in reference to the at least one subject matter expert candidate from the at least one result set.

14. The method of claim 11, further comprising:

extracting at least one name data from the at least one result set; and

listing the at least one name data for the at least one subject matter expert candidate data in relevancy-ranked order.

15. The method of claim 11, further comprising:

applying at least one inference filter to the at least one result set, wherein the at least one inference filter is at least one of a years of experience inference, a knowledge inventory inference, an employment stability inference, a team player characterization inference and a management readiness inference.

16. The method of claim 11, wherein the search query is a textual description of a job opportunity.

17. The method of claim 11, wherein the at least one subject matter expert candidate is at least one patent professional.

18. The method of claim 11, wherein the at least one data collection is of technical literature.

19. The method of claim 11, further comprising:

compiling at least one document having more than one qualification data of the at least one subject matter expert candidate.

20. The method of claim 11, further comprising:

accessing a salary database populated by a plurality of pay scale data; and

returning at least one pay scale data.

21. The method of claim 11, further comprising:

accessing a location database populated by a plurality of location data; and

returning at least one location data.

22. The method of claim 13, further comprising:

recording the at least one data in at least one table for use by a user.

23. A method for identifying patent professionals, comprising:

submitting a textual description of a job opportunity as a search query to at least one semantic database having a plurality of pseudo-vectors expressing a plurality of semantic concepts from at least one patent literature database populated by a plurality of patent literature data;

applying the search query to the at least one semantic database;

returning at least one result set having at least one patent literature data in relevancy-ranked order;

extracting at least one name data from the at least one patent literature data;

listing the at least one name data in relevancy-ranked order, whereby the at least one name data is checked for duplicates and merged

applying at least one inference filter to the at least one result set, wherein the at least one inference filter is at least one of a years of experience inference, a knowledge inventory inference, an employment stability inference, a team player characterization inference and a management readiness inference;

extracting at least one other data responsive to the at least one filter from the at least one patent literature database;

recording the at least one other data to at least one table;

displaying a list of the at least one name data, wherein the list is configured to be sortable; and

compiling a document containing a plurality of qualification data.