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Dimensionality reduction of features for text categorization
Author(s)
Jitpakdee, Parisut
Date Issued
December 1, 2007
Type
Conference Paper
Abstract
This paper proposes a new technique for dimensionality reduction of features for text categorization. Unlike conventional method, our phrase features are generated based on word sequences of different length (Multigrams) from phrases extracted from whole documents. Then, we utilize Odds ratio (OR) to perform phase feature selection. From preliminary experiments, the proposed techniques show better performance than that of conventional methods.
Citation
Proceedings of the 3rd IASTED International Conference on Advances in Computer Science and Technology Acst 2007, 506-509, 2007