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    題名: Mining fuzzy temporal association rules by item lifespans
    作者: Chun-Hao Chena;Guo-Cheng Lanb;Tzung-Pei Hong;Shih-Bin Lind
    關鍵詞: Fuzzy set;Fuzzy data mining;Fuzzy temporal association rule;Item lifespan
    日期: 2016-04
    上傳時間: 2017-12-22 02:10:12 (UTC+8)
    出版者: Elsevier BV
    摘要: Data mining is the process of extracting desirable knowledge or interesting patterns from existing databases for specific purposes. In real-world applications, transactions may contain quantitative values and each item may have a lifespan from a temporal database. In this paper, we thus propose a data mining algorithm for deriving fuzzy temporal association rules. It first transforms each quantitative value into a fuzzy set using the given membership functions. Meanwhile, item lifespans are collected and recorded in a temporal information table through a transformation process. The algorithm then calculates the scalar cardinality of each linguistic term of each item. A mining process based on fuzzy counts and item lifespans is then performed to find fuzzy temporal association rules. Experiments are finally performed on two simulation datasets and the foodmart dataset to show the effectiveness and the efficiency of the proposed approach.
    關聯: Applied Soft Computing 41, pp.265–274
    DOI: 10.1016/j.asoc.2016.01.008
    顯示於類別:[資訊工程學系暨研究所] 期刊論文

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