Querying and clustering Web pages about persons and organizations

Proceedings - IEEE/WIC International Conference on Web Intelligence, WI 2003

Volumn , Issue , 2003, Pages 344-350

  Ye, S ^a   Chua, T S ^a   Kei, J R ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

Biographies; Books; Clustering algorithms; Home computing; Internet; Partitioning algorithms; Resumes; Search engines; Tellurium; Web pages

Indexed keywords

ALGORITHMS; BIOGRAPHIES; DATA MINING; INTERNET; SEARCH ENGINES; TELLURIUM; TELLURIUM COMPOUNDS; WEBSITES; WORLD WIDE WEB;

BOOKS; CLUSTERING WEB PAGES; DECISION MODELING; HOME COMPUTING; PARTITIONING ALGORITHMS; PERSONS AND ORGANIZATIONS; RESUMES; WEB-BASED APPLICATIONS;

CLUSTERING ALGORITHMS;

EID: 70349671693     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WI.2003.1241214     Document Type: Conference Paper

References (18)

1. Text REtrieval Conference (TREC) Home Page, http://trec.nist.gov/
2. Ellen M. Voorhees, Donna Harman, Overview of TREC 2001, NIST, TREC 2001, pp1-15
3. N. Craswell, D Hawking, Overview of the TREC-2002 Web Track, TREC 2002, pp1-16
4. D. Hawking and N. Craswell, Overview of the TREC-2001 Web Track, TREC 2001, pp61-67
5. T. Westerveld, et al, Retrieving Web pages using Content, Links, URLs and Anchors, TREC 2001
6. N. Craswell, et al, Effective Site Finding using Link Anchor Information; SIGIR, 2001
7. W. Kraaij, et al, The Importance of Prior Probabilities for Entry Page Search, SIGIR2002
8. W. Xi, E. A. Fox, Machine Learning Approach for Home page Finding Task, TREC 2001, pp686-697
9. Min Zhang, et al, THU at TREC2002: Novelty, Web and Filtering, TREC 2002, pp29-42
10. MacFarlane, A. MacFarlane, Pliers at Trec 2002, page 311, TREC 2002, pp311-313
11. D. Boley, et al, Partitioning-based Clustering for Web Document Categorization, in: Decision Support System 27, 329-341, 1999
12. O. Zamir and O. Etzioni. Web document clustering: A feasibility demonstration. SIGIR'98, 1998
13. O. Zamir, O., Etzioni, Grouper: a dynamic clustering interface to Web search results, in Computer Networks, 31(11), pp1361-1374, 1999
14. M. Steinbach, G. Karypis, V. Kumar, A comparison of document clustering techniques. Text Mining Workshop, KDD, 2000.
15. G. Salton, M. J. McGill, Introduction to Modern Information Retrieval, McGraw-Hill, NY, 1983
16. K. Yang, Combining Text-, Link-, and Classification-based Retrieval Methods to Enhance Information Discovery on the Web, Ph D. thesis, UNC-CH., 2002
17. J. Picard, J. Savoy, Using Probabilistic Argumentation Systems to Search and Classify Web Sites, 24(3), pp33-41, Data Engineering Bulletin,2001
18. A.K. Jain, M. N. Murty, and P.J. Flynn, Data clustering: A review, ACM Computing Surveys, 31(3), pp264-323, 1999