It is a problem that established document categorization method reflects the semantic relation inaccurately at feature expression of document. For the purpose of solving this problem, we propose a genetic algorithm and C-Means clustering algorithm for choosing an appropriate set of fuzzy clustering for classification problems of documents. The aim of the proposed method is to find a minimum set of fuzzy cluster that can correctly classify all training documents. The number of fuzzy pseudo-partition and the shapes of the fuzzy membership functions that we use the classification criteria are determined by the genetic algorithms. Then, the classifier decides using fuzzy c-means clustering algorithms for documents classification. A solution obtained by the genetic algorithm is a set of fuzzy clustering, and its fitness function is determined by fuzzy membership function. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Youn, J. I., Eun, H. J., & Kim, Y. S. (2005). Fuzzy clustering for documents based on optimization of classifier using the genetic algorithm. In Lecture Notes in Computer Science (Vol. 3481, pp. 10–20). Springer Verlag. https://doi.org/10.1007/11424826_2
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