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收集所有交通大學研究人員與學生個人或團體所發表之各項學術著作，涵蓋期刊論文、教師專書、學位論文等項。;;Collections of Publications of NCTU Researchers and Students Like Journal Papers and Thesis.

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🏛️國立陽明交通大學機構典藏

Author: search.filters.author.Chen, Pei-LingSubject: search.filters.subject.Clustering

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    A Disk-Based Mining Algorithm for Frequent Pattern Discovery from Big Data in Distributed Computing Environments
    (2016-11-01)
    Lin, Kawuu W.
    ;
    Chung, Sheng-Hao
    ;
    Hsiao, Chun-Yuan
    ;
    Lin, Chun-Cheng
    ;
    Chen, Pei-Ling
    In distributed computing environments, frequent pattern mining by a multi-computing node can greatly improve mining efficiency. However, the drawback of memory limitations may cause interruption in the kernel and computing nodes when recursively building a frequent pattern (FP) tree or an FP-growth algorithm. In this paper, we propose disk-based FP-tree generation and node-based clustering mechanisms to solve the insufficient memory problem. Results from empirical evaluations show that the proposed method delivers excellent scalability.
  • Thumbnail Image
    Item type:Item,
    A Disk-Based Mining Algorithm for Frequent Pattern Discovery from Big Data in Distributed Computing Environments
    (2016-11)
    Lin, Kawuu W.
    ;
    Chung, Sheng-Hao
    ;
    Hsiao, Chun-Yuan
    ;
    Lin, Chun-Cheng
    ;
    Chen, Pei-Ling
    In distributed computing environments, frequent pattern mining by a multi-computing node can greatly improve mining efficiency. However, the drawback of memory limitations may cause interruption in the kernel and computing nodes when recursively building a frequent pattern (FP) tree or an FP-growth algorithm. In this paper, we propose disk-based FP-tree generation and node-based clustering mechanisms to solve the insufficient memory problem. Results from empirical evaluations show that the proposed method delivers excellent scalability.