Accurately interpreting clickthrough data as implicit feedback Thorsten Joachims, Laura Granka, Bing Pan, Helene Hembrooke, and Geri Gay   View Paper (PDF)   Return to Evaluation 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. BIBTEX @inproceedings{1076063,   author = {Thorsten Joachims and Laura Granka and Bing Pan and Helene Hembrooke and Geri Gay},   title = {Accurately interpreting clickthrough data as implicit feedback},   booktitle = {SIGIR '05: Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval},   year = {2005},   isbn = {1-59593-034-5},   pages = {154--161},   location = {Salvador, Brazil},   doi = {http://doi.acm.org/10.1145/1076034.1076063},   publisher = {ACM Press},   address = {New York, NY, USA},    } ©2006 Association for Computing Machinery