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序號 | 學年期 | 教師動態 |
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1 | 95/2 | 軍訓室 張忠義 少校教官於 期刊論文 發佈 An Algorithm for Mining Strong Negative Fuzzy Sequential Patterns , [95-2] ：An Algorithm for Mining Strong Negative Fuzzy Sequential Patterns期刊論文An Algorithm for Mining Strong Negative Fuzzy Sequential PatternsLin, Nancy P.; Hao, Wei-hua, Chen, Hung-jen; Chang, Chung-i; Chueh, Hao-en淡江大學資訊工程學系;軍訓室Braga: North Atlantic University UnionInternational Journal of Computers 3(1), pp.167-172Many 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. Besi |

2 | 95/2 | 資工系 闕豪恩 助理教授於 期刊論文 發佈 An Algorithm for Mining Strong Negative Fuzzy Sequential Patterns , [95-2] ：An Algorithm for Mining Strong Negative Fuzzy Sequential Patterns期刊論文An Algorithm for Mining Strong Negative Fuzzy Sequential PatternsLin, Nancy P.; Hao, Wei-hua, Chen, Hung-jen; Chang, Chung-i; Chueh, Hao-en淡江大學資訊工程學系;軍訓室Braga: North Atlantic University UnionInternational Journal of Computers 3(1), pp.167-172Many 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. Besi |

3 | 95/2 | 資工系 陳宏任 講師於 期刊論文 發佈 An Algorithm for Mining Strong Negative Fuzzy Sequential Patterns , [95-2] ：An Algorithm for Mining Strong Negative Fuzzy Sequential Patterns期刊論文An Algorithm for Mining Strong Negative Fuzzy Sequential PatternsLin, Nancy P.; Hao, Wei-hua, Chen, Hung-jen; Chang, Chung-i; Chueh, Hao-en淡江大學資訊工程學系;軍訓室Braga: North Atlantic University UnionInternational Journal of Computers 3(1), pp.167-172Many 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. Besi |

4 | 95/2 | 資工系 郝維華 講師於 期刊論文 發佈 An Algorithm for Mining Strong Negative Fuzzy Sequential Patterns , [95-2] ：An Algorithm for Mining Strong Negative Fuzzy Sequential Patterns期刊論文An Algorithm for Mining Strong Negative Fuzzy Sequential PatternsLin, Nancy P.; Hao, Wei-hua, Chen, Hung-jen; Chang, Chung-i; Chueh, Hao-en淡江大學資訊工程學系;軍訓室Braga: North Atlantic University UnionInternational Journal of Computers 3(1), pp.167-172Many 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. Besi |

5 | 95/2 | 資工系 林丕靜 副教授於 期刊論文 發佈 An Algorithm for Mining Strong Negative Fuzzy Sequential Patterns , [95-2] ：An Algorithm for Mining Strong Negative Fuzzy Sequential Patterns期刊論文An Algorithm for Mining Strong Negative Fuzzy Sequential PatternsLin, Nancy P.; Hao, Wei-hua, Chen, Hung-jen; Chang, Chung-i; Chueh, Hao-en淡江大學資訊工程學系;軍訓室Braga: North Atlantic University UnionInternational Journal of Computers 3(1), pp.167-172Many 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. Besi |

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