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A decision-tree-based symbolic rule induction system for text categorization

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4 Author(s)
Johnson, D.E. ; IBM Research Division, Thomas J. Watson Research Center, P.O. Box 218, Yorktown Heights, New York 10598, USA ; Oles, F.J. ; Zhang, T. ; Goetz, T.

We present a decision-tree-based symbolic rule induction system for categorizing text documents automatically. Our method for rule induction involves the novel combination of (1) a fast decision tree induction algorithm especially suited to text data and (2) a new method for converting a decision tree to a rule set that is simplified, but still logically equivalent to, the original tree. We report experimental results on the use of this system on some practical problems.

Note: The Institute of Electrical and Electronics Engineers, Incorporated is distributing this Article with permission of the International Business Machines Corporation (IBM) who is the exclusive owner. The recipient of this Article may not assign, sublicense, lease, rent or otherwise transfer, reproduce, prepare derivative works, publicly display or perform, or distribute the Article.  

Published in:

IBM Systems Journal  (Volume:41 ,  Issue: 3 )