Accurately interpreting clickthrough data as implicit feedback
Acm Sigir Forum, 2017•dl.acm.org
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.
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.
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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