关键词: 文本分类, 特征选择, 风险决策

Abstract: The selection of feature words would severely affect the accuracy of text categorization. In view of this situation, this paper proposes a novel text feature selection approach based on dynamic venture decision. This approach uses utility function to evaluate the utility value of each feature word in text categorization, then uses venture decision method to work out the loss of each feature word, finally selects some feature words with lower losses for reducing dimensions. The proposed approach is applied to the spam filtering and Web category in Chinese. The experimental results on several benchmark datasets show that the proposed feature selection approach can select those feature words which will influence the classification results greatly. In so doing, the accuracy of text classification can be improved significantly.

Key words: text categorization, feature selection, venture decision