On the use of fuzzy rules to text document classification

This work presents the integration of a fuzzy method and text mining to obtain an approach that enables the text documents classification to be closer to the user needs. The aim of this work is to develop a mechanism to reduce the high dimensionality of the attribute-value matrix obtained from the documents and, with this, to manage the imprecision and uncertainty using fuzzy rules to classify text documents. Some experiments have been run using different domains in order to validate the proposed approach and to compare the results with the ones obtained with the Ibk, J48, Naive Bayes and OneR classification methods. The advantages of the method, the experiments and the results obtained are discussed.