PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Galavotti L., Sebastiani F., Simi M. Feature selection and negative evidence in automated text categorization. [Poster Paper]. In: ACM-KDD-00 Workshop on Text Mining (Boston, 2000). Proceedings, Marko Grobelnik, Dunja Mladeni and Natasa Milic-Frayling (eds.). 2000.
 
 
Abstract
(English)
We tackle two different problems of text categorization (TC), namely feature selection and classifier induction. We propose a novel FS technique, based on a simplified version of the X 2 statistics and a novel variant, based on the exploitation of negative evidence, of the well-known k-NN method. We report the results of systematic experimentation of these two methods performed on the standard Reuters-21578 benchmark.
Subject Text Mining
Information Extraction


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