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    題名: A Novel System for Mining Useful Correlation in Smart Home
    作者: Chen, Yi-Cheng;Peng, Wen-Chih;Lee, Wan-Chien
    貢獻者: 淡江大學資訊工程學系
    關鍵詞: correlation pattern;smart home;sequential pattern;time interval-based data;usage representation
    日期: 2013-12
    上傳時間: 2014-05-28 16:39:16 (UTC+8)
    摘要: Owing to the great advent of sensor technology, the usage data of appliances in a house can be logged and collected easily today. However, it is a challenge for the residents to visualize how these appliances are used. Thus, mining algorithms are much needed to discover appliance usage patterns. Most previous studies on usage pattern discovery are mainly focused on analyzing the patterns of single appliance rather than mining the usage correlation among appliances. In this paper, a novel system, namely, Correlation Pattern Mining System (CPMS), is developed to capture the usage patterns and correlations among appliances. With several new optimization techniques, CPMS can reduce the search space effectively and
    efficiently. Furthermore, the proposed algorithm is applied on a real-world dataset to show the practicability of correlation pattern mining.
    關聯: The 6th International Workshop on Domain Driven Data Mining (DDDM 2013) in conjunction with IEEE ICDM 2013, pp.357-364
    顯示於類別:[資訊工程學系暨研究所] 會議論文

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