Can Chinese web pages be classified with english data

Proceeding of the 17th International Conference on World Wide Web 2008, WWW'08

Volumn , Issue , 2008, Pages 969-978

  Ling, Xiao ^a   Xue, Gui Rong ^a   Dai, Wenyuan ^a   Jiang, Yun ^a   Yang, Qiang ^b   Yu, Yong ^a  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

^b HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Hong Kong)

Author keywords

Cross Language Classification; Information Bottleneck

Indexed keywords

INFORMATION THEORY; INTERNET; KNOWLEDGE BASED SYSTEMS; LEARNING ALGORITHMS; LEARNING SYSTEMS; LINGUISTICS;

CLASS LABELS; CROSS-LANGUAGE CLASSIFICATION; INFORMATION BOTTLENECK; INFORMATION BOTTLENECKS; LABELED DATUMS; LIMITED INFORMATIONS; LINGUISTIC REPRESENTATIONS; MACHINE LEARNING TECHNIQUES; MINING KNOWLEDGES; OPEN DIRECTORY PROJECTS; SEMANTIC INFORMATIONS; SUPERVISED CLASSIFIERS; WEB INFORMATIONS; WEB PAGES;

WORLD WIDE WEB;

EID: 57349129460     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1367497.1367628     Document Type: Conference Paper

References (32)

1. Google translator. http://www.google.com/language-tools.
2. A. Banerjee, I. Dhillon, J. Ghosh, S. Merugu, and D. S. Modha. A generalized maximum entropy approach to bregman co-clustering and matrix approximation. In Proceedings of the Tenth A CM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 509-514, 2004.
3. N. Bel, C. Koster, and M. Villegas. Cross-Lingual Text Categorization. Proceedings ECDL, 200:126-139, 2003.
4. A. Blum and T. Mitchell. Combining labeled and unlabeled data with co-training. In Proceedings of the Eleventh Annual Conference on Computational Learning Theory, pages 92-100, 1998.
5. B. E. Boser, I. Guyon, and V. Vapnik. A training algorithm for optimal margin classifiers. In Proceedings of the Fifth Annual Workshop on Computational Learning Theory, pages 144-152, 1992.
6. T. M. Cover and P. E. Hart. Nearest neighbor pattern classification. IEEE Transactions on Information Theory, 13:21-27, 1967.
7. T. M. Cover and J. A. Thomas. Elements of information theory. Wiley-Interscience, New York, NY, USA, 1991.
8. M. Day, C. Ong, and W. Hsu. Question Classification in English-Chinese Cross-Language Question Answering: An Integrated Genetic Algorithm and Machine Learning Approach. In Proceedings of the 2007 IEEE International Conference on Information Reuse and Integration, pages 203-208, 2007.
9. I. S. Dhillon, S. Mallela, and R. Kumar. Enhanced word clustering for hierarchical text classification. In Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 191-200, 2002.
10. I. S. Dhillon, S. Mallela, and D. S. Modha. Information-theoretic co-clustering. In Proceedings of the Ninth A CM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2003.
11. A. Gliozzo and C. Strapparava. Cross language Text Categorization by acquiring Multilingual Domain Models from Comparable Corpora. Proc. of the A CL Workshop on Building and Using Parallel Texts (in conjunction of ACL-05), 2005.
12. T. Joachims. SVM light. Software available at http://svmlight. Joachims.org.
13. T. Joachims. Transductive inference for text classification using support vector machines. In Proceedings of the Sixteenth International Conference on Machine Learning, pages 200-209, 1999.
14. S. Kullback and R. A. Leibler. On information and sufficiency. Annals of Mathematical Statistics, 22(l):79-86, 1951.
15. K. Lang. Newsweeder: Learning to filter netnews. In Proceedings of the Twelfth International Conference on Machine Learning, pages 331-339, 1995.
16. D. D. Lewis. Reuters-21578 test collection, http://www.daviddlewis.com/.
17. D. D. Lewis. Representation and learning in information retrieval. PhD thesis, Amherst, MA, USA, 1992.
18. Y. Li and J. Shawe-Taylor. Advanced learning algorithms for cross-language patent retrieval and classification. Information Processing and Management, 43(5):1183-1199, 2007.
19. Y. Liu, Y. Fu, M. Zhang, S. Ma, and L. Ru. Automatic search engine performance evaluation with click-through data analysis. Proceedings of the 16th international conference on World Wide Web, pages 1133-1134, 2007.
20. X. Ni, G. Xue, X. Ling, Y. Yu, and Q. Yang. Exploring in the weblog space by detecting informative and affective articles. Proceedings of the 16th international conference on World Wide Web, pages 281-290, 2007.
21. K. Nigam, A. K. McCallum, S. Thrun, and T. Mitchell. Text classification from labeled and unlabeled documents using em. Machine Learning, 39(2-3):103-134, 2000.
22. ODP. Open directory project, http://www.dmoz.com/.
23. J. Olsson, D. Oard, and J. Hajic. Cross-language text classification. Proceedings of the 28th annual international A CM SIGIR conference on Research and development in information retrieval, pages 645-646, 2005.
24. M. F. Porter. An algorithm for suffix stripping. Program, 14(3):130-137, 1980.
25. J. R. Quinlan. CJh5: Programs for Machine Learning. Morgan Kaufmann, 1993.
26. L. Rigutini, M. Maggini, and B. Liu. An em based training algorithm for cross-language text categorization. In Proceedings of the 2005 IEEE/WIG/A CM International Conference on Web Intelligence, pages 529-535, 2005.
27. N. Slonim. The Information Bottleneck: Theory and Applications. Unpublished doctoral dissertation, Hebrew University, Jerusalem, Israel, 2002.
28. N. Slonim and Y. Weiss. Maximum likelihood and the information bottleneck. Advances in Neural Information Processing Systems, 15, 2002.
29. N. Tishby, F. C. Pereira, and W. Bialek. The information bottleneck method. In Proceedings of the Thirty-seventh Annual Allerton Conference on Communication, Control and Computing, pages 368-377, 1999.
30. Y.-C. Wu, K.-C. Tsai, and J.-C. Yang. Two-pass named entity classification for cross language question answering. In Proceedings of NTCIR-6 Workshop Meeting, pages 168-174, 2007.
31. Y. Yang and J. O. Pedersen. A comparative study on feature selection in text categorization. In Proceedings of Fourteenth International Conference on Machine Learning, pages 144-152, 1997.
32. X. Zhu. Semi-supervised learning literature survey. Technical Report 1530, University of Wisconsin-Madison, 2006.