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	Provedor de dados AgEcon (1) Autor Dobrowiecki, Tadeusz (1) Pilaszy, Istvan (1) Palavra-chave Classifier ensembles (1) Machine learning (1) Research and Development/Tech Change/Emerging Technologies (1) Text categorization (1) Tipo do documento Journal Article (1) Ano 2007 (1) País United States (1) Idioma Inglês (1)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 1 Primeira ... 1 ... Última TEXT CATEGORIZATION USING ONLY FRAGMENTS OF DOCUMENTS AgEcon Pilaszy, Istvan; Dobrowiecki, Tadeusz. In this paper we presented a lot of experiments that examine how the particular parts of the documents do contribute to the performance of a classifier. We evaluated text classifiers on two very different text corpora. We conclude that some parts of the text are more important from the point of text classification performance. Giving higher weights to more important parts can increase the performance of the classifier. The question, that which parts are more or less important depends on the nature of the documents in the corpora. Some tasks that remains to be done: − More text corpora should be investigated. − In section 6.4 we optimized the number of features to be kept independent from the section. However, it could be optimized for each section. −... Tipo: Journal Article Palavras-chave: Machine learning; Text categorization; Classifier ensembles; Research and Development/Tech Change/Emerging Technologies. Ano: 2007 URL: http://purl.umn.edu/58927 Registros recuperados: 1 Primeira ... 1 ... Última

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