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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/98057


    Title: Mining Correlation Patterns among Appliances in Smart Home Environment
    Authors: Chen, Yi-Cheng;Chen, Chien-Chih;Peng, Wen-Chih;Lee, Wang-Chien
    Contributors: 淡江大學資訊工程學系
    Keywords: correlation pattern;smart home;sequential pattern;time intervalbased data;usage representation
    Date: 2014-05
    Issue Date: 2014-05-22 21:55:43 (UTC+8)
    Publisher: Springer
    Abstract: Since 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 algorithm, namely, Correlation Pattern Miner (CoPMiner), is developed to capture the usage patterns and correlations among appliances probabilistically. With several new optimization techniques, CoPMiner 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 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2014), pp.222-233
    Appears in Collections:[資訊工程學系暨研究所] 會議論文

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