会议专题

A Novel Text Representation Model for Text Classification

The text representation in text classification is usually a sequence of terms.As the number of terms becomes very high,it is greatly time-consuming to perform existed text categorization tasks.In this paper we presented a novel text representation model for text classification which greatly reduced the required resources.This model represents text with several features.Each feature corresponds to a theme that emerged from a set of related articles.We also introduce an efficient way to build the model.The proposed model has been applied to na飗e bayes classifier and experiments on Reuters-21578 corpus have shown that the efficiency is greatly improved without sacrificing classification accuracy even when the dimension of the input space is significantly reduced.

Jun Wang Yiming Zhou

School of Computer Science and Engineering,Beihang University Beijing,100191,P.R .China School of Computer Science and Engineering Beihang University ,Beijing,100191,P.R.China

国际会议

第一届智能网络与智能系统国际会议(ICINIS 2008)(The First International Conference on Intelligent Networks and Intelligent Systems)

武汉

英文

2008-11-01(万方平台首次上网日期,不代表论文的发表时间)