Discovering Time-Interval Sequential Patterns by a Pattern Growth Approach with Confidence Constraints

Huan-Jyh Shyur ； Chichang Jou ； Chi-Bin Cheng ； Chih-Yu Yen

《International Journal of Information and Management Sciences》 27卷2期 (2016/06) Pp. 129-145

https://doi.org/10.6186/IJIMS.2016.27.2.4

並列摘要

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.

並列關鍵字

Sequential pattern mining ； time-interval sequential patterns ； pattern growth ； confidence

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