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    請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/17388

    題名: An Algorithm for Mining Strong Negative Fuzzy Sequential Patterns
    作者: Lin, Nancy P.;Hao, Wei-hua, Chen, Hung-jen;Chang, Chung-i;Chueh, Hao-en
    貢獻者: 淡江大學資訊工程學系;軍訓室
    關鍵詞: Fuzzy itemset;sequential pattern;fuzzy sequential pattern;negative sequential pattern
    日期: 2007-03
    上傳時間: 2013-06-07 10:46:58 (UTC+8)
    出版者: Braga: North Atlantic University Union
    摘要: Many methods have been proposed for mining fuzzy sequential patterns. However, most of conventional methods only consider the occurrences of fuzzy itemsets in sequences. The fuzzy sequential patterns discovered by these methods are called as positive fuzzy sequential patterns. In practice, the absences of frequent fuzzy itemsets in sequences may imply significant information. We call a fuzzy sequential pattern as a negative fuzzy sequential pattern, if it also expresses the absences of fuzzy itemsets in a sequence. In this paper, we proposed a method for mining negative fuzzy sequential patterns, called NFSPM. In our method, the absences of fuzzy itemsets are also considered. Besides, only sequences with high degree of interestingness can be selected as negative fuzzy sequential patterns. An example was taken to illustrate the process of the algorithm NFSPM. The result showed that our algorithm could prune a lot of redundant candidates, and could extract meaningful fuzzy sequential patterns from a large number of frequent sequences.
    關聯: International Journal of Computers 3(1), pp.167-172
    顯示於類別:[軍訓室] 期刊論文
    [資訊工程學系暨研究所] 期刊論文


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