Sequential Pattern Mining with Time Intervals

  • Yu Hirate
  • Hayato Yamana
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3918)


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.


Sequential Pattern Pattern Mining Frequent Sequence Sensitive Pattern Sequential Pattern Mining 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yu Hirate
    • 1
  • Hayato Yamana
    • 1
  1. 1.Dept. of Computer ScienceWaseda UniversityTokyoJapan

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