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Volume 41, Number 3, 2002
Artificial Intelligence
 Table of contents: arrowHTML arrowPDF arrowASCII   This article: arrowHTML arrowPDF arrowASCII arrowCopyright info
   

A decision-tree-based symbolic rule induction system for text categorization - References
by D. E. Johnson, F. J. Oles, T. Zhang and T. Goetz

Cited references

  1. S. M. Weiss, C. Apte, F. Damerau, D. E. Johnson, F. J. Oles, T. Goetz, and T. Hampp, “Maximizing Text-Mining Performance,” IEEE Intelligent Systems 14, 63–69 (1999).
  2. A. McCallum and K. Nigam, “A Comparison of Event Models for Naive Bayes Text Classification,” Proceedings, AAAI Workshop on Learning for Text Categorization, Madison, WI (July 26–27, 1998), pp. 41–48.
  3. Y. Yang, “An Evaluation of Statistical Approaches to Text Categorization,” Information Retrieval Journal 1, 69–90 (1999).
  4. T. Joachims, “Text Categorization with Support Vector Machines: Learning with Many Relevant Features,” Proceedings, 10th European Conference on Machine Learning, Chemnitz, Germany (April 21–24, 1998), pp. 137–142.
  5. S. Dumais, J. Platt, D. Heckerman, and M. Sahami, “Inductive Learning Algorithms and Representations for Text Categorization,” Proceedings, 7th ACM International Conference on Information and Knowledge Management, Washington, DC (November 3–7, 1988), pp. 148–155.
  6. C. Apte, F. Damerau, and S. M. Weiss, “Automated Learning of Decision Rules for Text Categorization,” ACM Transactions on Information Systems 12, 233–251 (1994).
  7. J. R. Quinlan, C4.5: Programs for Machine Learning, Morgan Kaufmann Publishers, San Francisco, CA (1993).
  8. L. Breiman, J. H. Friedman, R. A. Olshen, and C. J. Stone, Classification and Regression Trees, Wadsworth Advanced Books and Software, Belmont, CA (1984).
  9. J. Gehrke, R. Ramakrishnan, and V. Ganti, “Rainforest—A Framework for Fast Decision Tree Construction of Large Datasets,” Data Mining and Knowledge Discovery 12, No. 2/3, 127–162 (2000).
  10. Y. Yang, J. Carbonell, R. Brown, T. Pierce, B. Archibald, and X. Liu, “Learning Approaches for Detecting and Tracking News Events,” IEEE Intelligent Systems 14, No. 4, 32–43 (1999).
  11. See http://www.daviddlewis.com/resources/testcollections/reuters21578/.
  12. F. M. J. Willems, Y. M. Shtarkov, and T. J. Tjalkens, “The Context Tree Weighting Method: Basic Properties,” IEEE Transactions on Information Theory 41, No. 3, 653–664 (1995).
  13. T. Zhang, “Compression by Model Combination,” Proceedings, IEEE Data Compression Conference, Snowbird, Utah (March 30–April 1, 1998), pp. 319–328.
  14. B. Carlin and T. Louis, Bayes and Empirical Bayes Methods for Data Analysis, Chapman and Hall, New York (1996).
  15. Y. Yang and J. P. Pedersen, “A Comparative Study on Feature Selection in Text Categorization,” Proceedings, 14th AAAI International Conference on Machine Learning, Nashville, TN (July 8–12, 1997).
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