Similarity Measures to Compare Episodes in Modeled Traces

  • Raafat Zarka
  • Amélie Cordier
  • Elöd Egyed-Zsigmond
  • Luc Lamontagne
  • Alain Mille
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7969)


This paper reports on a similarity measure to compare episodes in modeled traces. A modeled trace is a structured record of observations captured from users’ interactions with a computer system. An episode is a sub-part of the modeled trace, describing a particular task performed by the user. Our method relies on the definition of a similarity measure for comparing elements of episodes, combined with the implementation of the Smith-Waterman Algorithm for comparison of episodes. This algorithm is both accurate in terms of temporal sequencing and tolerant to noise generally found in the traces that we deal with. Our evaluations show that our approach offers quite satisfactory comparison quality and response time. We illustrate its use in the context of an application for video sequences recommendation.


Similarity Measures Modeled Traces Recommendations Edit Distance Human Computer Interaction 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Raafat Zarka
    • 1
    • 2
  • Amélie Cordier
    • 1
    • 3
  • Elöd Egyed-Zsigmond
    • 1
    • 2
  • Luc Lamontagne
    • 4
  • Alain Mille
    • 1
    • 3
  1. 1.CNRSUniversité de LyonFrance
  2. 2.LIRIS, UMR5205INSA-LyonFrance
  3. 3.LIRIS, UMR5205Université Lyon 1France
  4. 4.Department of Computer Science and Software EngineeringUniversité LavalCanada

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