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Do User (Browse and Click) Sessions Relate to Their Questions in a Domain-Specific Collection?

  • Jeremy Steinhauer
  • Lois M. L. Delcambre
  • Marianne Lykke
  • Marit Kristine Ådland
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8092)

Abstract

We seek to improve information retrieval in a domain-specific collection by clustering user sessions as recorded in a click log and then classifying later user sessions in real-time. As a preliminary step, we explore the main assumption of this approach: whether user sessions in such a site relate to the question that they are answering. The contribution of this paper is the evaluation of the suitability of common machine learning measurements (measuring the distance between two sessions) to distinguish sessions of users searching for the answer to same or different questions. We found that sessions for people answering the same question are significantly different than those answering different questions, but results are dependent on the distance measure used. We explain why some distance metrics performed better than others.

Keywords

Distance Measure User Session Distance Score Average Pairwise Distance Cosine Vector 
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 2013

Authors and Affiliations

  • Jeremy Steinhauer
    • 1
  • Lois M. L. Delcambre
    • 1
  • Marianne Lykke
    • 2
  • Marit Kristine Ådland
    • 3
  1. 1.Department of Computer SciencePortland State UniversityPortlandU.S.A.
  2. 2.Aalborg UniversityAalborgDenmark
  3. 3.Dept. of Library and Information ScienceOslo University CollegeOsloNorway

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