Auteurs: | » Abdelmalek Amine » ELBERRICHI Zakaria » Michel Simonet » Malki Mimoun | |
Type : | Revue Internationale | |
Nom du journal : | INFOCOMP Journal of Computer Science ISSN: | |
Volume : 7 | Issue: 1 | Pages: 27-35 |
Lien : » | ||
Publié le : | 01-03-2008 |
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.