Sequential Pattern Mining with Time Intervals
Sequential pattern mining can be used to extract frequent sequences maintaining their transaction order. As conventional sequential pattern mining methods do not consider transaction occurrence time intervals, it is impossible to predict the time intervals of any two transactions extracted as frequent sequences. Thus, from extracted sequential patterns, although users are able to predict what events will occur, they are not able to predict when the events will occur. Here, we propose a new sequential pattern mining method that considers time intervals. Using Japanese earthquake data, we confirmed that our method is able to extract new types of frequent sequences that are not extracted by conventional sequential pattern mining methods.
KeywordsSequential Pattern Pattern Mining Frequent Sequence Sensitive Pattern Sequential Pattern Mining
Unable to display preview. Download preview PDF.
- 1.Agrawal, R., Srikant, R.: Mining Sequential Patterns. In: Proc. of ICDE’95, pp. 3–14 (1995)Google Scholar
- 2.J. Pei, J. Han, B. Mortazavi-Asl, H. Pinto, Q. Chen, U. Dayal, and -C. M. Hsu, “PrefixSpan: Mining Sequential Patterns Efficiently by Prefix-Projected Pattern Growth,” In Proc of ICDE’01, pp.215-224, 2001. Google Scholar
- 3.Zaki, M.J.: Sequence Mining in Categorical Domains: Incorporating Constraints. In: Proc. of CIKM’00, pp. 422–429 (2000)Google Scholar
- 4.Pei, J., Han, J., Wang, W.: Mining Sequential Pattern with Constraints in Large Databases. In: Proc. of CIKM’02, pp. 18–25 (2002)Google Scholar
- 6.K-NET Kyoshin Network, http://www.k-net.bosai.go.jp