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Uncertainty Interval Temporal Sequences Extraction

  • Asma Ben Zakour
  • Sofian Maabout
  • Mohamed Mosbah
  • Marc Sistiaga
Part of the Communications in Computer and Information Science book series (CCIS, volume 285)

Abstract

Searching for frequent sequential patterns has been used in several domains. We note that times granularities are more or less important with regards to the application domain. In this paper we propose a frequent interval time sequences (ITS) extraction technique from discrete temporal sequences using a sliding window approach to relax time constraints. The extracted sequences offer an interesting overview of the original data by allowing a temporal leeway on the extraction process. We formalize the ITS extraction under classical time and support constraints and conduct some experiments on synthetic data for validating our proposal.

Keywords

Window Size Sequence Extraction Frequent Pattern Temporal Sequence Event Occurrence 
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 2012

Authors and Affiliations

  • Asma Ben Zakour
    • 1
    • 2
  • Sofian Maabout
    • 1
  • Mohamed Mosbah
    • 1
  • Marc Sistiaga
    • 2
  1. 1.LaBRIUniversity of Bordeaux, CNRS UMR 5800France
  2. 2.2MoRO SolutionsBidartFrance

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