Stylistic and lexical co-training for Web block classification

Proceedings of the Interntational Workshop on Web Information and Data Management

Volumn , Issue , 2004, Pages 136-143

  Lee, Chee How ^a   Kan, Min Yen ^a   Lai, Sandra ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

Co training; Lexical and stylistic learners; PARCELS; Web page block classification; Web page division

Indexed keywords

ALGORITHMS; COMPUTER SOFTWARE; DATA STRUCTURES; HTML; INFORMATION RETRIEVAL; MATHEMATICAL MODELS;

LEXICAL AND STYLISTIC LEARNERS; LEXICAL CO-TRAINING; PARCELS; WEB PAGE BLOCK CLASSIFICATION; WEB PAGE DIVISION;

WORLD WIDE WEB;

EID: 18744391668     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1031453.1031478     Document Type: Conference Paper

References (18)

1. Blum, A. and Mitchell, T. Combining labeled and unlabeled data with co-training. In Proc. of COLT '98, pages 92-100. 1998.
2. th WWW Conference, Hawaii, 2002, pp. 232 - 241
3. Hurst, M. and Douglas, S. (1997). Layout & Language: Preliminary experiments in assigning logical structure to table cells. In Proc. of Applied Natural Language Processing Conf., Washington, 1997, pages 217-220.
4. Ghani, R. Combining labeled and unlabeled data for text classification with a large number of categories. In Proc. of IEEE Int'l Conf. on Data Mining, pages 597-598. 2001.
5. nd Int'l Conf. on Multi-model Interfaces, 1999.
6. Ivory, M.Y. Characteristics of Web Site Designs: Reality vs. Recommendation. In Proc. of HCI Int'l Conf., 2003.
7. Nigam, K. and Ghani, R. Analyzing the effectiveness and applicability of Co-Training. In Proc. of the 9th Int'l Conf. on Information and Knowledge Management, pages 86-93. 2000.
8. Ramaswamy, L., Iyengar, A., Liu, L. and Douglis, F. Automatic Detection of Fragments in Dynamically Generated Web Pages. In Proc. of WWW '04, pages 443-454. New York, USA. May 2004.
9. Reis, D., Golgher, P. B., da Silva, A. and Laender, A. H. F. Automatic Web News Extraction Using Tree Edit Distance. In Proc. of WWW '04, pages 502-511. New York, USA. May 2004.
10. Salton, G. and Buckley, C. Term-weighting approaches in automatic text retrieval. Information Processing and Management. 24:513-523. 1988.
11. Schapire, R. E. and Singer, Y. BoosTexter: A boosting-based system for text categorization. Machine Learning, 39 (2/3), pages 135-168. 2000.
12. Shih, L. K. and Karger, D. R. Using URLs and Table Layout for Web Classification Tasks. In Proc. of WWW '04, pages 193-202. New York, USA. May 2004.
13. Song, R., Liu, H., Wen, J.-R. and Ma, W.-Y. Learning Block Importance Models for Web Pages. In Proc. of WWW '04, pages 203-211. New York, USA. May 2004.
14. Wong, W. and Fu, A. W., Finding Structure and Characteristics of Web Documents for Classification. In Proc. of ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery (DMKD). Dallas, USA. 2000.
15. Xi, W., Zhang, B., Chen, Z., Lu, Y., Yan, S. and Ma, W.-Y. Link Fusion: A Unified Link Analysis Framework for Multi-Type Interrelated Data Objects. In Proc. of WWW '04, pages 319-327. New York, USA. May 2004.
16. Yin, X. and Lee, W.-S. Using Link Analysis to Improve Layout on Mobile Devices. In Proc. of WWW '04, pages 338-344. New York, USA. May 2004.
17. Ye, S. and Chua, T.-S., Detecting and Partitioning of Data Objects in Complex Web Pages, In Proc. of Web Intelligence '04, Beijing. China. September 2004.
18. Yu, S., Cai, D., Wen, J.-R., and Ma, W.-Y., Improving pseudo-relevance feedback in web information retrieval using web page segmentation. In Proc. of WWW '03, pages 11-18. Budapest, Hungary. May 2003.