A New Probabilistic Model for Bayes Document Classification

摘要：

　　In this paper,we propose a new probabilistic model of naive Bayes method which can be used in text classification.This method not only takes account of the frequency of feature words,but also considers those important words do not appear in the test document,which overcomes the shortcoming of the Multi-variate Bernoulli event Model(MBM) and Multinomial event Model(MM).Experiments show that the method proposed in this paper has better classification result than those traditional methods.

关键词： na(i)ve Bayes text classification Multi-variate Bernoulli event Model Multinomial event Model

作者: Ya-Shu Liu Han-Bing Yan

作者单位: Department of Computer Science Beijing University of Civil Engineering and Architecture Beijing,P.R. National Institute of Network and Information Security National Computer network Emergency Response

会议类型: 国际会议

会议名称: 2013 2nd International Conference on Computer Science and Electronics Engineering(ICCSEE2013)(2013年第二届计算机科学与电子工程国际会议)

会议地点: 杭州

会议语种:英文

页码: 1240-1243

在线出版日期: 2013-03-22（万方平台首次上网日期，不代表论文的发表时间）