Text Categorization Based on Semantic Cluster-Hidden Markov Models

摘要：

　　A new text categorization algorithm based on Hidden Markov Model is proposed.At first, semantic clusters are obtained from training data set.The association between semantic clusters is modeled as Hidden Markov Model.Combining with the forward algorithm, the strategy could realize automatic text categorization.From the simulation, the proposed text categorization algorithm is better in categorization precision.Moreover, it works well independent of the number of considered categories compared to the priori art algorithms.

关键词： text categorization Hidden Markov models Semantic Cluster text serialization

作者: Fang Li Tao Dong

作者单位: Intelligence Engineering Lab, Beijing University of Chemical Technology,Beijing 100029, China

会议类型: 国际会议

会议名称: 4th international Conference,ICSI2013(第4届群体智能国际会议)

会议地点: 哈尔滨

会议语种:英文

页码: 200-207

在线出版日期: 2013-06-12（万方平台首次上网日期，不代表论文的发表时间）