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  • 标题:An Efficient Depth-first Search Algorithm for Extracting Frequent Diamond Episodes from Event Sequences
  • 本地全文:下载
  • 作者:Takashi Katoh ; Hiroki Arimura ; Kouichi Hirata
  • 期刊名称:Information and Media Technologies
  • 电子版ISSN:1881-0896
  • 出版年度:2010
  • 卷号:5
  • 期号:2
  • 页码:459-470
  • DOI:10.11185/imt.5.459
  • 出版社:Information and Media Technologies Editorial Board
  • 摘要:In this paper, we study the problem of mining frequent diamond episodes efficiently from an input event sequence with sliding a window. Here, a diamond episode is of the form a → E → b , which means that every event of E follows an event a and is followed by an event b . Then, we design a polynomial-delay and polynomial-space algorithm PolyFreqDmd that finds all of the frequent diamond episodes without duplicates from an event sequence in O (|Σ|2 l ) time per an episode and in O (|Σ|+ l ) space, where Σ and l are an alphabet and the length of the event sequence, respectively. Finally, we give experimental results on artificial and real-world event sequences with varying several mining parameters to evaluate the efficiency of the algorithm.
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