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|Title: ||Evaluation and Comparison of Concept Based and N-Grams Based Text Clustering Using SOM|
|???metadata.dc.creator???: ||Amine, Abdelmalek|
|Keywords: ||Text clustering, Self-Organizing Maps of Kohonen, n-grams, concept, similarity, Reuters21578.|
|Publisher: ||Editora da UFLA|
|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.|
|Appears in Collections:||Infocomp|
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