A data mining approach to discovering reliable sequential patterns
學年 102
學期 1
出版（發表）日期 2013-08-01
作品名稱 A data mining approach to discovering reliable sequential patterns
作品名稱（其他語言）
著者 Shyur, Huan-Jyh; Jou, Chichang; Chang, Keng
單位 淡江大學資訊管理學系
出版者 New York: Elsevier Inc.
著錄名稱、卷期、頁數 The Journal of Systems and Software 86(8), pp.2196–2203
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.
關鍵字
語言 en_US
ISSN 1873-1228 0164-1212
期刊性質 國外
收錄於 SCI
產學合作
通訊作者 Shyur, Huan-Jyh
審稿制度 是
國別 USA
公開徵稿
出版型式 紙本,電子版
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