一种基于传统VSM和词共现概念的中文文本聚类的研究

RESEARCH OF CHINESE TEXT CLUSTERING BASEDON TRADITIONAL VSM AND TERM Co-OCCURRENCE

提出了一种利用传统向量空间模型VSM(VectorSpaceModel)和词共现概念共同表示文档特征的新方法,并将该方法应用于基于平面划分的中文文本聚类中.通过实验,表明基于传统VSM和词共现概念的文本聚类方法与传统的单纯基于关键词集的VSM文本聚类方法相比具有更好的聚类性能,具有一定的实用价值.

This paper proposes a new text-representing method based on Traditional VSM and Term Co-occurrence Concept., and the authors apply the method to cluster the Chinese document by a partitional algorithm. The experiment results show the new text-representing method based on Traditional VSM and Term Co-occurrence Concept. Is more effective than the traditional text-representing method only based on