1998 TextCategorizationWithSVMs

• (Joachims, 1998) ⇒ Thorsten Joachims. (1998). “Text Categorization with Support Vector Machines: Learning with Many Relevant Features.” In: Proceedings of the European Conference on Machine Learning (ECML 1998). doi:10.1007/BFb0026683

Subject Headings: Text Classification Algorithm, Support Vector Machine

Cited By

• ~4415 http://scholar.google.com/scholar?q=%22Text+Categorization+with+Support+Vector+Machines%3A+Learning+with+Many+Relevant+Features%22+1998

2002

• (Sebastiani, 2002) ⇒ Fabrizio Sebastiani. (2002). “Machine Learning in Automated Text Categorization.” In: Association of Computing Machinery Computing Surveys, 34 (1), 1-47.

Quotes

Abstract

This paper explores the use of Support Vector Machines (SVMs) for learning text classifiers from examples. It analyzes the particular properties of learning with text data and identies why SVMs are appropriate for this task. Empirical results support the theoretical findings. SVMs achieve substantial improvements over the currently best performing methods and behave robustly over a variety of different learning tasks. Furthermore, they are fully automatic, eliminating the need for manual parameter tuning.

References

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• 3. Thorsten Joachims. Text categorization with support vector machines: Learning with many relevant features. Technical Report 23, Universit?at Dortmund, LS VIII, 1997.
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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
1998 TextCategorizationWithSVMs	Thorsten Joachims			Text Categorization with Support Vector Machines: Learning with Many Relevant Features			http://www.cs.cornell.edu/People/tj/publications/joachims 98a.pdf