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
Link To Document :
بازگشت