Using Connections Between Users and Documents to Rank Documents in an Enterprise Search System

• US 20080016052A1
• Filed: 08/01/2006
• Published: 01/17/2008
• Est. Priority Date: 07/14/2006
• Status: Abandoned Application

• Current Assignee: Oracle International Corporation (Oracle Corporation)
• Original Assignee: BEA Systems Incorporated (Oracle Corporation)
• Inventors: Frieden, Kurt
• Application Number:
  US11/461,549
• Publication Number:
  US 20080016052A1
• Time in Patent Office: Days
• US Class Current: 707/5
• CPC Class Codes: G06F 16/3331 Query processing

Abstract

Ranks for documents can be made by calculating coefficients indicating connections between users and documents. The coefficients can be used to calculate search-independent rank values for the documents. The search-independent rank values can be combined with term matching indications to get a total relevance of the document.

Claims

1. A computer-implemented method of creating ranks for documents comprising:

calculating coefficients indicating connections between users and documents; and

using the coefficients to calculate rank values for the documents.

2. The computer-implemented method of claim 1, wherein the coefficients are part of a matrix indicating connections between users and documents.

3. The computer-implemented method of claim 1, wherein the coefficients are used to form a matrix to calculate a modified matrix used to calculate an eigenvector solution containing the ranks.

4. The computer-implemented method of claim 1, wherein the ranks are part of an eigenvector solution to a matrix equation.

5. The computer-implemented method of claim 1, wherein additional coefficients indicate connections between tags and users and documents.

6. The computer-implemented method of claim 1, wherein connections between users and documents include an authoring relationship.

7. The computer-implemented method of claim 1, wherein connections between documents and users include an access relationship.

8. The computer-implemented method of claim 1, wherein the using step including (a) for each row of a core data structure:

reading a row of the core data structure into local memory,

inflating the row,

converting the row into a row of a damped matrix,

multiplying the row of a damped matrix by a current vector to get a value of the next vector;

(b) comparing the next vector to the current vector, wherein

if the difference is greater than an error value, set the next vector as the current vector and repeat step (a);

if the difference is less than an error value, determine rank values from the next vector.

9. The computer-implemented method of claim 8, wherein the damped matrix is column stochastic.

10. The computer-implemented method of claim 8, wherein the damped matrix is positive.

20. The computer-implemented method of claim 1, wherein the using step includes (a) for each row of a core data structure:

reading a row of the core data structure into local memory,

inflating the row,

converting the row into a row of a damped matrix,

multiplying the row of a damped matrix by a current vector to get a value of the next vector;

(b) comparing the next vector to the current vector, wherein

if the difference is greater than an error value, set the next vector as the current vector and repeat step (a);

if the difference is less than an error value, determine rank values from the next vector.

21. The computer-implemented method of claim 20, wherein the damped matrix is column stochastic.

22. The computer-implemented method of claim 20, wherein the damped matrix is positive.

11. The computer-implemented method comprising:

associating documents with tags; and

using connections between the tags and documents to determine rank value for the documents.

12. The computer-implemented method of claim 11, wherein connections between users, tags and documents are used to determine the rank values for the documents.

13. The computer-implemented method of claim 11, further comprising calculating coefficients indicating connections between the tags and documents and using the coefficients to calculate rank values for the documents.

14. The computer-implemented method of claim 11, wherein the coefficients are part of a matrix indicating connections between users and documents.

15. The computer-implemented method of claim 11, wherein the coefficients are used to form a matrix to calculate a modified matrix used to calculate an eigenvector solution containing the ranks.

16. The computer-implemented method of claim 11, wherein the ranks are part of an eigenvector solution to a matrix equation.

17. The computer-implemented method of claim 11, wherein connections between users and documents include an authoring relationship.

18. The computer-implemented method of claim 11, wherein the connection between tags and documents include the association of a tag with the document.

19. The computer-implemented method of claim 11, wherein tags are displayed with the size of the tag indicating the tag rank.