articleAug 15, 2005Closed access

Accurately interpreting clickthrough data as implicit feedback

Cornell University · Stanford University · +1 more institution

Indexed incrossref

Abstract

This paper examines the reliability of implicit feedback generated from clickthrough data in WWW search. Analyzing the users' decision process using eyetracking and comparing implicit feedback against manual relevance judgments, we conclude that clicks are informative but biased. While this makes the interpretation of clicks as absolute relevance judgments difficult, we show that relative preferences derived from clicks are reasonably accurate on average.

Citation impact

1,395
total citations
FWCI
158.54
Percentile
100%
References
30
Citations per year

Authors

5

Topics & keywords

Keywords
  • Relevance (law)
  • Computer science
  • Reliability (semiconductor)
  • Relevance feedback
  • Interpretation (philosophy)
  • Process (computing)
  • Artificial intelligence
  • Natural language processing
UN Sustainable Development Goals
  • Peace, Justice and strong institutions
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