Mining Strong Positive and Negative Sequential Patterns
學年 96
學期 2
出版(發表)日期 2008-03-01
作品名稱 Mining Strong Positive and Negative Sequential Patterns
作品名稱(其他語言) 探勘強勢正向及負向序列型樣
著者 Lin, Nancy P.; Chen, Hung-jen; Hao, Wei-hua; Chueh, Hao-en; Chang, Chung-i
單位 淡江大學軍訓室; 淡江大學資訊工程學系
出版者 Zographou: World Scientific and Engineering Academy and Society
著錄名稱、卷期、頁數 WSEAS Transations on Computers 7(3), pp.119-124
摘要 In data mining field, sequential pattern mining can be applied in divers applications such as basket analysis, web access patterns analysis, and quality control in manufactory engineering, etc. Many methods have been proposed for mining sequential patterns. However, conventional methods only consider the occurrences of itemsets in customer sequences. The sequential patterns discovered by these methods are called as positive sequential patterns, i.e., such sequential patterns only represent the occurrences of itemsets. In practice, the absence of a frequent itemset in a sequence may imply significant information. We call a sequential pattern as negative sequential pattern, which also represents the absence of itemsets in a sequence. The two major difficulties in mining sequential patterns, especially negative ones, are that there may be huge number of candidates generated, and most of them are meaningless. In this paper, we proposed a method for mining strong positive and negative sequential patterns, called PNSPM. In our method, the absences of itemsets are also considered. Besides, only sequences with high degree of interestingness will be selected as strong sequential patterns. An example was taken to illustrate the process of PNSPM. The result showed that PNSPM could prune a lot of redundant candidates, and could extract meaningful sequential patterns from a large number of frequent sequences.
關鍵字 Data mining, Itemset, Frequent sequence, Positive sequential pattern, Negative sequential pattern, Strong sequential pattern
語言 en
ISSN 1109-2750 2224-2872
期刊性質 國外
收錄於 EI
產學合作
通訊作者
審稿制度
國別 GRC
公開徵稿
出版型式 紙本
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