A New Efficient Text Clustering Ensemble Algorithm Based on Semantic Sequences

摘要：

　　The idea of cluster ensemble is combining the multiple clustering of a data set into a consensus clustering for improving the quality and robustness of results.In this paper, a new text clustering ensemble (TCE) algorithm is proposed.First, text clustering results of applying k-means and semantic sequence algorithms are produced.Then in order to generate co-association matrix between semantic sequences, the clustering results are combined based on the overlap coefficient similarity concept.Finally, the ultimate clusters are obtained by merging documents corresponding to similar semantic sequence on this matrix.Experiment results of proposed method on real data sets are compared with other clustering results produced by individual clustering algorithms.It is showed that TCE is efficient especially on long documents set.

关键词： text clustering ensemble overlap coefficient similarity semantic sequence co-association matrix

作者: Zhonghui Feng Junpeng Bao Kaikai Liu

作者单位: Institute of Computer Software, Xian Jiaotong University, Xian 710049, 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: 183-190

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）