Authors: Joachims, Thorsten
Title: Text categorization with support vector machines
Language (ISO): en
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 identifies, why SVMs are appropriate for this task. Empirical results support the theoretical findings. SVMs achieve substantial improvements over the currently best performing methods and they behave robustly over a variety of different learning tasks. Furthermore, they are fully automatic, eliminating the need for manual parameter tuning. The paper is written in English.
URI: http://hdl.handle.net/2003/2595
http://dx.doi.org/10.17877/DE290R-5097
Issue Date: 1999-10-29
Publisher: Universität Dortmund
Appears in Collections:LS 08 Künstliche Intelligenz

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