articleAug 15, 2005Closed access
Accurately interpreting clickthrough data as implicit feedback
Cornell University · Stanford University · +1 more institution
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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.
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5Topics & keywords
Topics
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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