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ACM Transactions on Information Systems (TOIS), Volume 12 Issue 3, July 1994

Automated learning of decision rules for text categorization
Chidanand Apté, Fred Damerau, Sholom M. Weiss
Pages: 233-251
DOI: 10.1145/183422.183423
We describe the results of extensive experiments using optimized rule-based induction methods on large document collections. The goal of these methods is to discover automatically classification patterns that can be used for general document...

An example-based mapping method for text categorization and retrieval
Yiming Yang, Christopher G. Chute
Pages: 252-277
DOI: 10.1145/183422.183424
A unified model for text categorization and text retrieval is introduced. We use a training set of manually categorized documents to learn word-category associations, and use these associations to predict the categories of arbitrary documents....

Text categorization for multiple users based on semantic features from a machine-readable dictionary
Elizabeth D. Liddy, Woojin Paik, Edmund S. Yu
Pages: 278-295
DOI: 10.1145/183422.183425
The text categorization module described here provides a front-end filtering function for the larger DR-LINK text retrieval system [Liddy and Myaeing 1993]. The model evaluates a large incoming stream of documents to determine which documents...

Information extraction as a basis for high-precision text classification
Ellen Riloff, Wendy Lehnert
Pages: 296-333
DOI: 10.1145/183422.183428
We describe an approach to text classification that represents a compromise between traditional word-based techniques and in-depth natural language processing. Our approach uses a natural language processing task called “information...