Using Tags in an Enterprise Search System

• US 20080016098A1
• Filed: 08/01/2006
• Published: 01/17/2008
• Est. Priority Date: 07/14/2006
• Status: Active Grant

• Current Assignee: Oracle International Corporation (Oracle Corporation)
• Original Assignee: BEA Systems Incorporated (Oracle Corporation)
• Inventors: Quezada, Jose, Mahendra, Samir, Farhang, Dax, Frieden, Kurt
• Granted Patent: US 7,873,641 B2
• Time in Patent Office: Days
• US Class Current: 707/102
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques

Abstract

An interface can allow for associating documents with tags. A search system can use connections between the tags and documents to determine 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 comprising:

automatically creating initial tags for documents in an enterprise system based on document location information;

using the tags to provide user access to the documents.

2. The computer-implemented method of claim 1, wherein the tags can be clicked on to access documents tagged the tag.

3. The computer implemented method of claim 1, wherein existing document metadata is used to create initial tags.

4. The computer implemented method of claim 1, further comprising, a search system that uses connections between the tags and documents to determine rank values for the documents.

5. The computer-implemented method of claim 1, wherein the connectors between users tags, and documents are used to determine the rank values for the documents.

6. The computer implemented method of claim 1, further comprising calculating coefficients indicating connections between the tags and documents and using the coefficients to calculate rank values for the documents.

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

8. 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.

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

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

11. The computer-implemented method of claim 1, wherein the connection between tags and documents include an association of a tag with the document.

12. The computer implemented method of claim 1, wherein tags are displayed with the size of the tag indicating the tag rank.

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

reading a row of a 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.

14. The computer-implemented method of claim 13, wherein the damped matrix is column stochastic.

15. The computer-implemented method of claims 13, wherein the damped matrix is positive.

16. A computer-implemented method comprising:

automatically creating initial tags for documents in an enterprise system at least some of the initial tags using translational rules such that if a first term is associated with the document, a second term is used as the initial tag; and

using the tags to provide use access to the documents.

17. The computer-implemented method of claim 16, wherein the first term is a folder name.

18. The computer-implemented method of claim 16, wherein the first term is metadata.

19. The computer-implemented method of claim 16, wherein the first term is a document hierarclly name.

20. The computer implemented method of claim 16, further comprising a searchi system that uses connections between the tags and documents to determine rank values for the docutments.

21. The comptuter-implemented method of claim 16, wherein the connectors between users tags, and documients are used to determine the rank values for the documents.

22. The computer implemented method of claim 16, further comprising calculating coefficients indicating connections between the tags and documents and using the coefficients to calculate rank values for the documents.

23. The computer-implemented method of claim 16, wherein the coefficients are part of a matrix indicating connections between users and documents.

24. The computer-implemented method of claim 16, wherein the coefficients are used to form a matrix to calculate a modified matrix used to calculate an eigenvectors solution containing the ranks.

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

26. The computer-implemented method of claim 16, wherein connections between users and documents include an authoring relationship.

27. The computer-implemented method of claim 16, wherein the connection between tags and documents include an association of a tag with the document.

28. The computer implemented method of claim 16, wherein tags are displayed with the size of the tag indicating the tag rank.

29. The computer implemented method of claim 16, wherein the using step including (a) for each row of the core data structure:

reading a row of a 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.

30. The computer-implemented method of claim 29, wherein the damped matrix is column stochastic.

31. The computer-implemented method of claims 29, wherein the damped matrix is positive.