Discovering time-interval sequential patterns by a pattern growth approach with confidence constraints

doi:10.6186/IJIMS.2016.27.2.4

淡江大學機構典藏 > 商管學院 > 資訊管理學系暨研究所 > 期刊論文 > Item 987654321/106992

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題名:	Discovering time-interval sequential patterns by a pattern growth approach with confidence constraints
作者:	Shyur, Huan-Jyh;Jou, Chi-Chang;Cheng, Chi-Bin;Yen, Chih-Yu
關鍵詞:	Sequential pattern mining;time-interval sequential patterns;pattern growth;confidence
日期:	2016-07-15
上傳時間:	2016-08-15
出版者:	淡江大學管理科學學系
摘要:	Sequential pattern mining is to discover frequent sequential patterns in a sequence database. The technique is applied to fields such as web click-stream mining, failure forecast, and traf- fic analysis. Conventional sequential pattern-mining approaches generally focus only the orders of items; however, the time interval between two consecutive events can be a valuable information when the time of the occurrence of an event is concerned. This study extends the concept of the well-known pattern growth approach, PrefixSpan algorithm, to propose a novel sequential pattern mining approach for sequential patterns with time intervals. Unlike the other time-interval sequential pattern-mining algorithms, the approach concerns the time for the next event to occur more than the timing information with its precedent events. To obtain a more reliable sequential pattern, a new measure of the confidence of a sequential pattern is defined. Experiments are conducted to evaluate the performance of the proposed approach.
關聯:	International Journal of Information and Management Sciences 27(2), p.129-145
DOI:	10.6186/IJIMS.2016.27.2.4
顯示於類別:	[資訊管理學系暨研究所] 期刊論文

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