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2006 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops
Distributed Mining of Constrained Patterns from Wireless Sensor Data
Hong Kong, China
December 18-December 22
ISBN: 0-7695-2749-3
Carson Kai-Sang Leung, The University of Manitoba, Canada
Quamrul I. Khan, The University of Manitoba, Canada
Boyu Hao, The University of Manitoba, Canada
With the advance in technology, wireless sensor networks have been widely used in many application areas such as agricultural and environmental monitoring. Sensors distributed in these networks serve as good sources for data. This calls for distributed data mining, which searches for implicit, previously unknown, and potentially useful patterns that might be embedded in the distributed data. Many existing distributed data mining algorithms do not allow users to express the patterns to be mined according to their intension via the use of constraints. Consequently, these unconstrained mining algorithms can yield numerous patterns that are not interesting to users. In this paper, we propose an efficient tree-based system for mining patterns that satisfy user-defined constraints from a distributed environment such as a wireless sensor network. Experimental results show effectiveness of our proposed system.
Citation:
Carson Kai-Sang Leung, Quamrul I. Khan, Boyu Hao, "Distributed Mining of Constrained Patterns from Wireless Sensor Data," wi-iatw, pp.248-251, 2006 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops, 2006
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