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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/98142

    Title: A Novel System for Mining Useful Correlation in Smart Home
    Authors: Chen, Yi-Cheng;Peng, Wen-Chih;Lee, Wan-Chien
    Contributors: 淡江大學資訊工程學系
    Keywords: correlation pattern;smart home;sequential pattern;time interval-based data;usage representation
    Date: 2013-12
    Issue Date: 2014-05-28 16:39:16 (UTC+8)
    Abstract: 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.
    Relation: The 6th International Workshop on Domain Driven Data Mining (DDDM 2013) in conjunction with IEEE ICDM 2013, pp.357-364
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Proceeding

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