T.Joachims Optimizing Search Engines using Clickthrough Data 133–142 2002 ThorstenJoachims LauraGranka BingPan HeleneHembrooke GeriGay Accurately interpreting clickthrough data as implicit feedback ACM 154–161 2005 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. F.Radlinski T.Joachims Active Exploration for Learning Rankings from Clickthrough Data 2007 F.Radlinski T.Joachims Query Chains: Learning to Rank from Implicit Feedback 239–248 2005