• DocumentCode
    22485
  • Title

    Examining the Limits of Crowdsourcing for Relevance Assessment

  • Author

    Clough, Paul ; Sanderson, M. ; Jiayu Tang ; Gollins, T. ; Warner, A.

  • Volume
    17
  • Issue
    4
  • fYear
    2013
  • fDate
    July-Aug. 2013
  • Firstpage
    32
  • Lastpage
    38
  • Abstract
    Evaluation is instrumental to developing and managing effective information retrieval systems. For this process, enlisting crowdsourcing has proven viable. However, less understood are crowdsourcing´s limits for evaluation, particularly for domain-specific search. The authors compare relevance assessments gathered using crowdsourcing with those from a domain expert to evaluate different search engines in a large government archive. Although crowdsourced judgments rank the tested search engines in the same order as expert judgments, crowdsourced workers appear unable to distinguish different levels of highly accurate search results the way expert assessors can.
  • Keywords
    information retrieval; search engines; crowdsourced judgments; crowdsourced workers; crowdsourcing; domain-specific search; evaluation; expert judgments; government archive; information retrieval systems; limit examination; relevance assessment; search engines; Crowdsourcing; Information retrieval; Internet; Navigation; Performance evaluation; Search engines; Search methods; System analysis and design; crowdsourcing; information search and retrieval; performance of systems;
  • fLanguage
    English
  • Journal_Title
    Internet Computing, IEEE
  • Publisher
    ieee
  • ISSN
    1089-7801
  • Type

    jour

  • DOI
    10.1109/MIC.2012.95
  • Filename
    6231614