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    题名: A cloud-based system for dynamically capturing appliance usage relations
    作者: 陳以錚;Chen, Yi-Cheng;Chang, Shih-Hao;Liao, Wei-Hsun;Liu, Jianquan;Watanobe, Yutaka
    贡献者: 管理學院資訊管理學系
    关键词: Correlation;Data mining;Dynamic tests;Dynamical systems;Dynamics;Internet;Smart buildings;Strategy
    日期: 2016-01-01
    上传时间: 2026-04-23 13:13:03 (UTC+8)
    出版者: Inderscience Enterprises Ltd;Inderscience Publishers (IEL)
    摘要: 摘要: Nowadays, owing to the great advent of sensor technology, data can be collected easily. Mining Internet of Things (IoT) data has attracted researchers' attention owing to its practicability. Mining smart home data is one significant application in the IoT domain. Generally, the usage data of appliances in a smart environment are generated progressively; visualising how appliances are used from huge amount of data is a challenging issue. Hence, an algorithm is needed to dynamically discover appliance usage patterns. Prior studies on usage pattern discovery are mainly focused on discovering patterns while ignoring the dynamic maintenance of mined results. In this paper, a cloud-based system, Dynamic Correlation Mining System (DCMS), is developed to incrementally capture the usage correlations among appliances in a smart home environment. Furthermore, several pruning strategies are proposed to effectively reduce the search space. Experimental results indicate that the developed system is efficient in execution time and possesses great scalability. Subsequent application of DCMS on a real data set also demonstrates the practicability of mining smart home data.
    其他題名: ijwgs
    出版者: Inderscience Publishers (IEL)
    出版日期: 2016
    出處: International Journal of Web and Grid Services, 2016, Vol.12 (3), p.257-272
    版權: Copyright © 2016 Inderscience Enterprises Ltd.
    識別號: ISSN: 1741-1106
    識別號: EISSN: 1741-1114
    識別號: DOI: 10.1504/IJWGS.2016.079161
    显示于类别:[資訊管理學系] 期刊論文

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