DocumentCode
3262161
Title
MovStream: An efficient algorithm for monitoring clusters evolving in data streams
Author
Tang, Liang ; Tang, Chang-jie ; Duan, Lei ; Li, Chuan ; Jiang, Ye-xi ; Zeng, Chun-qiu ; Zhu, Jun
Author_Institution
Sch. of Comput. Sci., Sichuan Univ., Chengdu
fYear
2008
fDate
26-28 Aug. 2008
Firstpage
582
Lastpage
587
Abstract
Monitoring cluster evolution in data streams is a major research topic in data streams mining. Previous clustering methods for evolving data streams focus on global clustering result. It may lose critical information about individual cluster. This paper introduces some basic movements of evolution of an individual cluster. Based on the measurement of the movements, a novel algorithm called MovStream is proposed to monitor clusterspsila evolving in data streams. The experimental results on real datasets show that our MovStream algorithm surpasses the well-known CluStream algorithm by 25-50% in accuracy and one order of magnitude in efficiency.
Keywords
data mining; pattern clustering; cluster evolution monitoring; data stream mining; movstream algorithm; Biomedical monitoring; Birth disorders; Clustering algorithms; Clustering methods; Computer science; Computerized monitoring; Data mining; Event detection; Gaussian distribution; Motion measurement;
fLanguage
English
Publisher
ieee
Conference_Titel
Granular Computing, 2008. GrC 2008. IEEE International Conference on
Conference_Location
Hangzhou
Print_ISBN
978-1-4244-2512-9
Electronic_ISBN
978-1-4244-2513-6
Type
conf
DOI
10.1109/GRC.2008.4664715
Filename
4664715
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