High Quality Algorithm for Chinese Short Messages Text Clustering Based on Semantic

摘要：

　　Existing data clustering method lacks considering of latent similar information existing among words,and it leads to unsatisfactory clustering result.Aiming at Chinese short message text clustering,this paper proposes a clustering algorithm based on semantic.It offers Chinese concept,and the measuring methods to calculate the similarity degree about words and Chinese short message text.It completes the clustering of Chinese short messages text through fission downwards and mergence of twos upwards.Experimental results show that this algorithm has better clustering quality than traditional algorithm.

关键词： short messages text semantic concept similarity

作者: Fengxia Yang

作者单位: Department of Computer Science Cangzhou Normal University Cangzhou, China

会议类型: 国际会议

会议名称: 2012 2nd International Conference on Computer and Information Applications(ICCIA2012)(2012第二届计算机和信息应用国际会议)

会议地点: 太原

会议语种:英文

页码: 1263-1266

在线出版日期: 2012-12-08（万方平台首次上网日期，不代表论文的发表时间）