关键词: 文本分类, 特征选择, 遗传算法, 并行策略

Abstract: Feature selection is one of the key steps in text classification system.However，most of existing feature selection methods are serial and are inefficient timely to be applied to Chinese massive text data sets，so it is a hotspot how to improve efficiency of feature selection by means of parallel strategy.It detailedly designs a Parallel Genetic Algorithm（PGA） which is used to select features.The algorithm uses genetic algorithm to search features and calculates fitness of feature subsets in multiple computing nodes at the same time，so can acquire quickly feature subsets which are more representative.Experimental results show that the method is effective.

Key words: text categorization, feature selection, Genetic Algorithm（GA）, parallel strategy