Short Text Clustering Algorithm with Feature Keyword Expansion

摘要：

　　To solve the problem of sparse keywords and similarity drift in short text segments,this paper proposes short text clustering algorithm with feature keyword expansion (STCAFKE).The method can realize short text clustering by expanding feature keyword based on HowNet and combining K-means algorithm and density algorithm.It may add the number of text keyword with feature keyword expansion and increase text semantic features to realize short text clustering.Experimental results show that this algorithm has increased the short text clustering quality on precision and recall.

关键词： Short Text Feature Keyword Expansion HowNet Text Clustering Algorithm K-means

作者: Chunxia Jin Haiyan Zhou Qiuchan Bai

作者单位: Huaiyin Institute of Technology, Faculty of Computer Engineering, Huaiyin, China Huaiyin Institute of Technology, Faculty of Electronic and Electrical Engineering, Huaiyin, China

会议类型: 国际会议

会议名称: 2012 2nd international Conference on Materials Science and Information Technology(2012第二届材料科学与信息技术国际会议)(MSIT2012)

会议地点: 西安

会议语种:英文

页码: 1716-1720

在线出版日期: 2012-08-24（万方平台首次上网日期，不代表论文的发表时间）