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http://dx.doi.org/10.5391/JKIIS.2005.15.3.312

Ubiquitous Data Mining Using Hybrid Support Vector Machine  

Jun Sung-Hae (청주대학교 통계학과)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.15, no.3, 2005 , pp. 312-317 More about this Journal
Abstract
Ubiquitous computing has had an effect to politics, economics, society, culture, education and so forth. For effective management of huge Ubiquitous networks environment, various computers which are connected to networks has to decide automatic optimum with intelligence. Currently in many areas, data mining has been used effectively to construct intelligent systems. We proposed a hybrid support vector machine for Ubiquitous data mining which realized intelligent Ubiquitous computing environment. Many data were collected by sensor networks in Ubiquitous computing environment. There are many noises in these data. The aim of proposed method was to eliminate noises from stream data according to sensor networks. In experiment, we verified the performance of our proposed method by simulation data for Ubiquitous sensor networks.
Keywords
Hybrid Support Vector Machine;
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Times Cited By KSCI : 2  (Citation Analysis)
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