A NOVEL APPROACH TOWARDS BISECTING K-MEANS CLUSTERING ALGORITHM PARALLELISM

摘要：

Considering the insufficiency of clustering speed which exists in the selecting the initial centroids of bisecting K-means (BKM) clustering algorithm, the idea of selecting the two patterns with distance maximum as the initial cluster centroids is implemented.The results show that the clustering speed is better than that of BKM.An in-depth study and analysis is carried out on how to accelerate clustering in parallel computing system.According to the characteristics of BKM, the parallelism algorithm based on data parallelism is put forward.Undertaken experimental results show that the improvement of algorithm get ideal speed up performance and efficiency.

关键词： Data mining Clustering Bisecting k-means Parallelism

作者: ZHANG JUNWEI WANG NIANBIN HUANG SHAOBIN

作者单位: College of Computer Science and Technology Harbin Engineering University Harbin,China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer Technology and Development(2011第三届计算机技术与发展国际会议 ICCTD2011)

会议地点: 成都

会议语种:英文

页码: 840-846

在线出版日期: 2011-11-25（万方平台首次上网日期，不代表论文的发表时间）