15th European Conference on Artificial Intelligence
  July 21-26 2002     Lyon     France  
   

ECAI-2002 Conference Paper

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Empirical investigation of fast text classification over linguistic features

Roberto Basili, Alessandro Moschitti, Maria Teresa Pazienza

Recently, an original extension of the well-known Rocchio model (i.e. the Generalized Rocchio Classifier (GRC)) as a feature weighting method for text classification has been presented. The assessment of such a model requires a statistically motivated parameter estimation method and wider empirical evidence. In this paper, three different corpora have been adopted in two languages. Results suggest that GRC, integrating linguistic information, is a viable more efficient alternative to state-of-art TC systems.

Keywords: Information Retrieval, Natural Language Processing, Information Extraction, Machine Learning

Citation: Roberto Basili, Alessandro Moschitti, Maria Teresa Pazienza: Empirical investigation of fast text classification over linguistic features. In F. van Harmelen (ed.): ECAI2002, Proceedings of the 15th European Conference on Artificial Intelligence, IOS Press, Amsterdam, 2002, pp.485-489.


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ECAI-2002 is organised by the European Coordinating Committee for Artificial Intelligence (ECCAI) and hosted by the UniversitÚ Claude Bernard and INSA, Lyon, on behalf of Association Franšaise pour l'Intelligence Artificielle.