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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/98681

    Title: An Intelligent System for Mining and Maintaining Correlation Patterns among Appliances in Smart Home
    Authors: Yi-Cheng Chen;Julia Tzu-Ya Weng
    Contributors: 資訊工程學系暨研究所
    Keywords: sensor data analysis
    smart home
    correlation pattern
    intelligent system
    incremental mining
    Date: 2014-08-26
    Issue Date: 2014-09-10 01:56:38 (UTC+8)
    Abstract: Recently, due to the great advent of sensor
    technology, residents can collect the usage data of appliances in a house easily. However, with data progressively generating, it is still a challenge to visualize how these appliances are used. Thus, a mining and maintaining system is needed to incrementally discover appliance usage
    patterns. Most previous studies on usage
    pattern discovery are mainly focused on analyzing the patterns of single appliance and do not consider the incremental maintenance of mining results. In this paper, a novel system, namely, Dynamic Correlation Mining System (DCMS) is
    developed to capture and maintain the correlation patterns among appliances incrementally. The experimental results indicate that proposed system is efficient in execution time and possesses scalability. Furthermore, we apply DCMS on a real-world dataset to show the practicability.
    Relation: The 10-th Workshop on Wireless, Ad Hoc and Sensor Networks (WASN 2014)
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Proceeding

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