计算机工程与应用2011，Vol.47Issue(24)：129-131,3.DOI:10.3778/j.issn.1002-8331.2011.24.036
一种基于粗糙集文本自动分类的改进算法
Improved algorithm of automatic classification based on rough set
摘要
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 en-tropy.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.关键词
粗糙集/属性约简/文本分类Key words
rough set/attribute reduction/text classification分类
计算机与自动化引用本文复制引用
张保富,施化吉..一种基于粗糙集文本自动分类的改进算法[J].计算机工程与应用,2011,47(24):129-131,3.基金项目
国家自然科学基金(the National Natural Science Foundation of China under Grant No.60841003) （the National Natural Science Foundation of China under Grant No.60841003）
国家火炬计划项目(No.2004EB33006). （No.2004EB33006）
