文章基本信息

标题：Density Based Distribute Data Stream Clustering Algorithm
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作者：Gao, Bing ; Zhang, Jianpei
期刊名称：Journal of Software
印刷版ISSN：1796-217X
出版年度：2013
卷号：8
期号：2
页码：435-442
DOI：10.4304/jsw.8.2.435-442
语种：English
出版社：Academy Publisher
摘要：To solve the problem of distributed data streams clustering, the algorithm DB-DDSC (Density-Based Distribute Data Stream Clustering) was proposed. The algorithm consisted of two stages. First 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. Second designed the algorithm to generate global clusters by combining the local models at coordinator site. The DB-DDSC algorithm can find the the clusters of different shapes under the distributed data stream environment, avoid frequently sending data by using the test-update algorithm, and reduce the data transmission. The experiments show that the DB-DDSC algorithm is feasible and scale expandable.
关键词：data streams;data mining;clustering;distributed data stream