Discounted Cumulated Gain Based Evaluation of Multiple-Query IR Sessions

  • Kalervo Järvelin
  • Susan L. Price
  • Lois M. L. Delcambre
  • Marianne Lykke Nielsen
Conference paper

DOI: 10.1007/978-3-540-78646-7_4

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4956)
Cite this paper as:
Järvelin K., Price S.L., Delcambre L.M.L., Nielsen M.L. (2008) Discounted Cumulated Gain Based Evaluation of Multiple-Query IR Sessions. In: Macdonald C., Ounis I., Plachouras V., Ruthven I., White R.W. (eds) Advances in Information Retrieval. ECIR 2008. Lecture Notes in Computer Science, vol 4956. Springer, Berlin, Heidelberg

Abstract

IR research has a strong tradition of laboratory evaluation of systems. Such research is based on test collections, pre-defined test topics, and standard evaluation metrics. While recent research has emphasized the user viewpoint by proposing user-based metrics and non-binary relevance assessments, the methods are insufficient for truly user-based evaluation. The common assumption of a single query per topic and session poorly represents real life. On the other hand, one well-known metric for multiple queries per session, instance recall, does not capture early (within session) retrieval of (highly) relevant documents. We propose an extension to the Discounted Cumulated Gain (DCG) metric, the Session-based DCG (sDCG) metric for evaluation scenarios involving multiple query sessions, graded relevance assessments, and open-ended user effort including decisions to stop searching. The sDCG metric discounts relevant results from later queries within a session. We exemplify the sDCG metric with data from an interactive experiment, we discuss how the metric might be applied, and we present research questions for which the metric is helpful.

Keywords

Interactive IR evaluation metrics cumulated gain 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Kalervo Järvelin
    • 1
  • Susan L. Price
    • 2
  • Lois M. L. Delcambre
    • 2
  • Marianne Lykke Nielsen
    • 3
  1. 1.University of TampereFinland
  2. 2.Portland State UniversityUSA
  3. 3.Royal School of Library and Information ScienceDenmark

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