System and method for ranking reference documents

• US 20080126331A1
• Filed: 08/25/2006
• Published: 05/29/2008
• Est. Priority Date: 08/25/2006
• Status: Abandoned Application

• Current Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Original Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Inventors: Shepherd, Michael D.
• Application Number:
  US11/510,345
• Publication Number:
  US 20080126331A1
• Time in Patent Office: Days
• US Class Current: 707/5
• CPC Class Codes: G06F 16/31 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/3331 Query processing
• CPC Class Codes: G06F 16/34 Browsing; Visualisation therefor

Abstract

A method for knowledge mining a set of documents, wherein each particular document of the set of documents has been assigned a score based upon how many documents reference the particular document, is disclosed. The method includes entering search criteria into the knowledge mining application which then uses the search criteria to identify documents that match the search criteria within the set of documents, and receiving a list of the identified documents, wherein the list of identified documents are ranked by their score.

Claims

1. A knowledge base containing a set of documents, wherein at least:

some of the documents are referenced by other documents and wherein each referenced document is associated with a score based upon the number of other documents that reference the referenced document.

2. The knowledge base of claim 1, wherein each referenced document'"'"'s score is based solely upon the number of documents that directly reference the referenced document.

3. The knowledge base of claim 1, wherein each referenced document'"'"'s score is based upon the total number of documents that directly and indirectly reference the referenced document.

4. The method of claim 1, wherein the documents are web pages.

5. A method for knowledge mining a set of documents, comprising:

entering search criteria into a knowledge mining application which then uses the search criteria to identify documents that match the search criteria within the set of documents; and

receiving a list of the identified documents,

wherein the list of identified documents are ranked by a weighted reference score assigned to each identified document, and

wherein the weighted reference score for each particular document is based upon how many documents reference the particular document.

6. The method of claim 5, further comprising assigning each identified document a score based upon how many documents reference the particular document.

7. The method of claim 5, wherein each document in the set of documents already has a weighted reference score at the time the knowledge mining is performed.

8. The method of claim 5, wherein the search criteria includes semantic criteria.

9. The method of claim 5, wherein the weighted reference score is based upon how many documents directly reference the particular document.

10. The method of claim 5, wherein the weighted reference score is based upon how many documents directly and indirectly reference the particular document.

11. The method of claim 5, wherein the set of documents are a set of web pages.

12. A knowledge mining application that receives criteria for searching a set of documents, identifies a set of result documents within the set of documents that match the criteria, assigns a score to each result document based upon the number of documents that reference that result document, and ranks the order of the search results based upon the assigned score.

13. A method for searching a set of documents, comprising:

receiving search criteria;

identifying documents that match the search criteria;

assigning a weighted reference score to each identified document, wherein the weighted reference score is based upon the number of documents in the set of documents that reference the identified document; and

generating a list of the identified documents,

wherein the set of documents are ranked according to each document'"'"'s assigned weighted reference score.

14. The method of claim 13, further comprising generating a reference network for the set of documents.

15. The method of claim 13, wherein the search criteria includes semantic criteria.

16. The method of claim 13, wherein the weighted reference score is based upon how many documents directly reference the particular document.

17. The method of claim 13, wherein the weighted reference score is based upon how many documents directly and indirectly reference the particular document.

18. The method of claim 13, wherein the set of documents are a set of web pages.