Evaluation Methods for Rankings of Facetvalues for Faceted Search

  • Anne Schuth
  • Maarten Marx
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6941)


We introduce two metrics aimed at evaluating systems that select facetvalues for a faceted search interface. Facetvalues are the values of meta-data fields in semi-structured data and are commonly used to refine queries. It is often the case that there are more facetvalues than can be displayed to a user and thus a selection has to be made. Our metrics evaluate these selections based on binary relevant assessments for the documents in a collection. Both our metrics are based on Normalized Discounted Cumulated Gain, an often used Information Retrieval metric.


Relevant Document Discount Cumulate Gain Recursive Version Strict Linear Order Navigation Session 
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 2011

Authors and Affiliations

  • Anne Schuth
    • 1
  • Maarten Marx
    • 1
  1. 1.ISLAUniversity of AmsterdamThe Netherlands

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