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
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