关键词: 粗糙集, 属性约简, 文本分类

Abstract: The affect of automatic text categorization mostly relies on the selection of attribute feature.Aiming at the problem that the traditional feature selection method which filters features using frequency threshold would result in information loss and reduce the classification precision，a novel automatic text categorization method based on rough set is proposed.In the proposed method，the weighted attribute features discretization is carried out to form a decision table;selection of conditional attributes at the decision table is carried out on the basis of attribute significance which is based on dependency degree;the reduction of text attribute features is performed by heuristic algorithm which is based on conditional information entropy.Experimental results show that the proposed method removes large number of redundant attribute features，and improves the performance of text categorization without reducing classification precision.

Key words: rough set, attribute reduction, text classification