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Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/14967

Title: Evaluation and Comparison of Concept Based and N-Grams Based Text Clustering Using SOM
???metadata.dc.creator???: Amine, Abdelmalek
Elberrichi, Zakaria
Simonet, Michel
Malki, Mimoun
Keywords: Text clustering, Self-Organizing Maps of Kohonen, n-grams, concept, similarity, Reuters21578.
Publisher: Editora da UFLA
???metadata.dc.date???: 1-Mar-2008
Other Identifiers: http://www.dcc.ufla.br/infocomp/index.php/INFOCOMP/article/view/203
Description: With the great and rapidly growing number of documents available in digital form (Internet, library, CD-Rom…), the automatic classification of texts has become a significant research field and a fundamental task in document processing. This paper deals with unsupervised classification of textual documents also called text clustering using Self-Organizing Maps of Kohonen in two new situations: a conceptual representation of texts and a representation based on n-grams, instead of a representation based on words. The effects of these combinations are examined in several experiments using 4 measurements of similarity. The Reuters-21578 corpus is used for evaluation. The evaluation was done by using the F-measure and the entropy.
???metadata.dc.language???: eng
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