Text categorization based on fuzzy soft set theory
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part IV
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Using the maximum-minimum synthesis method to carry through the fuzzy reasoning and classification Web text could only keep the main information. Many secondary factors were neglected. Though this method could decrease the workload of calculation, the adaptability and credibility of its results was not satisfied. Here a modified fuzzy comprehensive weighted evaluation algorithm on sematic Web was proposed. That is, using the "comprehensive weighted model" operator given in the paper and establishing a fuzzy reasoning mechanism by synthetically considering the influence of each factor based on the weight coefficient to ensure the accuracy and credibility of the result. A calculation method modifying the weight of text feature item was given. Consideration of the words length and the words tag of the sematic Web feature items show that modified weights are beneficial to the efficiency of classification. It validated the feasibility of this algorithm through the comparison experiment between this modified algorithm on fuzzy comprehensive weighted evaluation reasoning and the traditional method on maximum-minimum synthesis reasoning.