A New Method of K-means Clustering Algorithm with Events Based on Variable Time Granularity

摘要：

　　According to the characteristics of Weibo event, this paper analyzes the advantages and disadvantages of the traditional K-means algorithm, and proposes the K-means clustering algorithm of events based on variable time granularity.The experiments show that the improved algorithm is more suitable for clustering analysis of Weibo event, improves the efficiency of clustering algorithm, and solves the initial cluster centers sensitive issue, compared with the traditional K-means algorithm.

关键词： Weibo events K-means time granularity the initial clustering centers

作者: Mengxing Huang Hongjing Lin

作者单位: College of Information Science &Technology Hainan University Haikou 570228, China

会议类型: 国际会议

会议名称: The 13th Web Information Systems and Applications Conference(第十三届全国web信息系统及其应用学术会议)(WISA2016)、The 1st Symposium on Big Data Processing and Analysis)( BDPA 2016)第一届全国大数据处理与分析学术研讨会、The 1st Workshop on Information System Security)(ISS2016)(第一届全国信息系统安全研讨会

会议地点: 武汉

会议语种:英文

页码: 41-44

在线出版日期: 2016-09-23（万方平台首次上网日期，不代表论文的发表时间）