Experiments on the Use of Feature Selection and Negative Evidence in Automated Text Categorization-Reference-Cited by-同舟云学术

Experiments on the Use of Feature Selection and Negative Evidence in Automated Text Categorization

Published:2000 Issue: Volume: Page:59-68
ISSN:0302-9743
Container-title:Research and Advanced Technology for Digital Libraries
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Author:

Galavotti Luigi,Sebastiani Fabrizio,Simi Maria

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/3-540-45268-0_6

Reference10 articles.

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2. Lect Notes Comput Sci;T. Joachims,1998

3. D. D. Lewis. Representation and learning in information retrieval. PhD thesis, Department of Computer Science, University of Massachusetts, Amherst, US, 1992.

4. H. T. Ng, W. B. Goh, and K. L. Low. Feature selection, perceptron learning, and a usability case study for text categorization. In N. J. Belkin, A. D. Narasimhalu, and P. Willett, editors, Proceedings of SIGIR-97, 20th ACM International Conference on Research and Development in Information Retrieval, pages 67–73, Philadelphia, US, 1997. ACM Press, New York, US.

5. R. E. Schapire, Y. Singer, and A. Singhal. Boosting and Rocchio applied to text filtering. In W. B. Croft, A. Moffat, C. J. van Rijsbergen, R. Wilkinson, and J. Zobel, editors, Proceedings of SIGIR-98, 21st ACM International Conference on Research and Development in Information Retrieval, pages 215–223, Melbourne, AU, 1998. ACM Press, New York, US.

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