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Title: Using IR techniques to improve Automated Text Classification
Authors: Gonçalves, Teresa
Quaresma, Paulo
Keywords: machine learning
Text classification
Issue Date: 2004
Publisher: Springer-Verlag
Abstract: This paper performs a study on the pre-processing phase of the automated text classification problem. We use the linear Support Vector Machine paradigm applied to datasets written in the English and the European Portuguese languages – the Reuters and the Portuguese Attorney General’s Office datasets, respectively. The study can be seen as a search, for the best document representa- tion, in three different axes: the feature reduction (using linguistic in- formation), the feature selection (using word frequencies) and the term weighting (using information retrieval measures).
Type: article
Appears in Collections:INF - Artigos em Livros de Actas/Proceedings

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