Volume 8 Number 2 (Feb. 2013)
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JSW 2013 Vol.8(2): 435-442 ISSN: 1796-217X
doi: 10.4304/jsw.8.2.435-442

Density Based Distribute Data Stream Clustering Algorithm

Bing Gao, Jianpei Zhang
College of Computer Science and Technology,HEU, Harbin, China

Abstract—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 densityconnected 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.

Index Terms—Data streams, data mining, clustering, distributed data stream.


Cite: Bing Gao, Jianpei Zhang, "Density Based Distribute Data Stream Clustering Algorithm," Journal of Software vol. 8, no. 2, pp. 435-442, 2013.

General Information

ISSN: 1796-217X (Online)
Frequency:  Quarterly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKIGoogle Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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