Systems and methods for classifying content using matrix factorization

• US 7,788,264 B2
• Filed: 10/10/2007
• Issued: 08/31/2010
• Est. Priority Date: 11/29/2006
• Status: Active Grant

• Current Assignee: NEC Corporation
• Original Assignee: NEC Laboratories America Inc (NEC Corporation)
• Inventors: Gong, Yihong, Zhu, Shenghuo, Yu, Kai, Chi, Yun
• Primary Examiner(s): Mahmoudi; Tony
• Assistant Examiner(s): Choi; Michele C
• Application Number:
  US11/869,899
• Publication Number:
  US 20090132901A1
• Time in Patent Office: 1,056 Days
• Field of Search: None
• US Class Current: 707/739
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques

Abstract

Systems and methods for classifying documents each having zero or more links thereto include generating a link matrix; generating a document term matrix; and jointly factorizing the document term matrix and the link matrix.

Claims

1. A computer-implemented method for classifying documents each having zero or more links thereto, comprising:

a. generating a link matrix;

b. generating a document term matrix;

c. jointly factorizing the document term matrix and the link matrix to classify the documents, wherein the link matrix is generated by matrix factorization to derive a feature representation Z of web pages based on analyzing a link matrix A, where said Z is an n×

l matrix with each row being an l-dimensional feature vector of a web page;

d. applying a factorization defined as;

2. The computer-implemented method of claim 1, comprising generating one or more indicative factors to represent the documents.

3. The computer-implemented method of claim 1, wherein the document comprises one of:

a Web page, an email, and a referenced document.

4. The computer-implemented method of claim 1, comprising using latent semantic space to represent the documents.

5. The computer-implemented method of claim 4, comprising mapping the documents to the latent semantic space by determining a link structure and content of the documents.

6. The computer-implemented method of claim 1, comprising representing the documents as vectors.

7. The computer-implemented method of claim 6, comprising classifying the vectors.

8. The computer-implemented method of claim 7, comprising generating one or more classification results.

9. The computer-implemented method of claim 6, comprising clustering the vectors.

10. The computer-implemented method of claim 9, comprising generating one or more clustering results.

11. The computer-implemented method of claim 1, comprising generating a document word co-occurrence matrix from the documents.

12. The computer-implemented method of claim 1, wherein the link matrix is generated by the matrix factorization to represent web pages as one or more principal factors of a link structure.

13. The computer-implemented method of claim 1, wherein generating the document term matrix comprises applying a bag-of-words approach.

14. The computer-implemented method of claim 1, comprising performing supervised matrix factorization.

15. The computer-implemented method of claim 14, comprising using data labels to guide the matrix factorization.

16. The computer-implemented method of claim 14, comprising determining a Tikhonov regularization.

17. The computer-implemented method of claim 16, comprising applying a gradient method.

18. The computer-implemented method of claim 1, comprising generating a response to a search query based on the jointly factorized document term and link matrices.