| 標題：A data mining approach to discovering reliable sequential patterns |
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| 學年 | 102 |
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| 學期 | 1 |
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| 出版（發表）日期 | 2013/08/01 |
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| 作品名稱 | A data mining approach to discovering reliable sequential patterns |
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| 作品名稱（其他語言） | |
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| 著者 | Shyur, Huan-Jyh; Jou, Chichang; Chang, Keng |
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| 單位 | 淡江大學資訊管理學系 |
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| 出版者 | New York: Elsevier Inc. |
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| 著錄名稱、卷期、頁數 | The Journal of Systems and Software 86(8), pp.2196–2203 |
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| 摘要 | Sequential pattern mining is a data mining method for obtaining frequent sequential patterns in a sequential database. Conventional sequence data mining methods could be divided into two categories: Apriori-like methods and pattern growth methods. In a sequential pattern, probability of time between two adjacent events could provide valuable information for decision-makers. As far as we know, there has been no methodology developed to extract this probability in the sequential pattern mining process. We extend the PrefixSpan algorithm and propose a new sequential pattern mining approach: P-PrefixSpan. Besides minimum support-count constraint, this approach imposes minimum time-probability constraint, so that fewer but more reliable patterns will be obtained. P-PrefixSpan is compared with PrefixSpan in terms of number of patterns obtained and execution efficiency. Our experimental results show that P-PrefixSpan is an efficient and scalable method for sequential pattern mining. |
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| 關鍵字 | |
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| 語言 | 英文(美國) |
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| ISSN | 1873-1228;0164-1212 |
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| 期刊性質 | 國外 |
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| 收錄於 | SCI; |
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| 產學合作 | |
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| 通訊作者 | Shyur, Huan-Jyh |
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| 審稿制度 | 是 |
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| 國別 | 美國 |
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| 公開徵稿 | |
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| 出版型式 | 紙本,電子版 |
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| 相關連結 | |
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| SDGs | |
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