Context-sensitive Learning Methods for Text Categorization.

William W. Cohen, Yoram Singer: Context-sensitive Learning Methods for Text Categorization. SIGIR 1996: 307-315
  author    = {William W. Cohen and
               Yoram Singer},
  title     = {Context-sensitive Learning Methods for Text Categorization},
  booktitle = {SIGIR},
  year      = {1996},
  pages     = {307-315},
  ee        = {db/conf/sigir/CohenS96.html},
  bibsource = {DBLP,}


Two recently implemented machine learning algorithms, RIPPER and sleeping experts for phrases, are evaluated on a number of large text categorization problems. These algorithms both construct classifiers that allow the "context" of a word w to affect how (or even whether) the presence or absence of w will contribute to a classification. However, RIPPER and sleeping experts differ radically in many other respects: differences include different notions as to what constitutes a context, different ways of combining contexts to construct a classifier, different methods to search for a combination of contexts; and different criteria as to what contexts should be included in such a combination. In spite of these differences, both RIPPER and sleeping experts perform extremely well across a wide variety of categorization problems, generally outperforming previously applied learning methods. We view this result as a confirmation of the usefulness of classifiers that represent contextual information.

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Hans-Peter Frei, Donna Harman, Peter Schäuble, Ross Wilkinson (Eds.): Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR'96, August 18-22, 1996, Zurich, Switzerland (Special Issue of the SIGIR Forum). ACM 1996, ISBN 0-89791-792-8
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Referenced by

  1. Soumen Chakrabarti, Byron Dom, Rakesh Agrawal, Prabhakar Raghavan: Scalable Feature Selection, Classification and Signature Generation for Organizing Large Text Databases into Hierarchical Topic Taxonomies. VLDB J. 7(3): 163-178(1998)
  2. William W. Cohen: Integration of Heterogeneous Databases Without Common Domains Using Queries Based on Textual Similarity. SIGMOD Conference 1998: 201-212
  3. Soumen Chakrabarti, Byron Dom, Piotr Indyk: Enhanced Hypertext Categorization Using Hyperlinks. SIGMOD Conference 1998: 307-318
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