计算机应用研究2012，Vol.29Issue(8)：2845-2848,4.DOI:10.3969/j.issn.1001-3695.2012.08.011
一种基于代表点的分布式数据流聚类算法
Representative-based distribute data stream clustering algorithm
摘要
Abstract
To find the clusters of different shapes under the distributed data streams environment, this paper proposed the representative-based clustering algorithm. First, it presented the concept of circular-point based on the representative points and designed the iterative algorithm to find the density-connected circular-points, then generated the local model at the remote site. Secondly it designed the algorithm to generate global clusters by combining the local models at coordinator site. The experimental results on real and synthetic datasets demonstrate that the algorithm can find the clusters in different shapes and reduce the data transmission by using representative points, while avoiding frequently sending data through the test-update strategy.关键词
分布式数据流/数据挖掘/聚类/聚类演化/代表点Key words
distributed data stream/data mining/clustering/cluster evolving/representative point分类
信息技术与安全科学引用本文复制引用
高兵,张健沛,杨静..一种基于代表点的分布式数据流聚类算法[J].计算机应用研究,2012,29(8):2845-2848,4.基金项目
国家自然科学基金资助项目(61073043) （61073043）
黑龙江省自然科学基金资助项目(F201023) （F201023）
