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.
Description
In this paper, Joachims investigate different ways to generate pairwise preference based on clickthough log. The experiments show that as interpreted as relative preference, clickthrough is consistent with explicit judgment.
%0 Conference Paper
%1 joachims_accurately_2005
%A Joachims, Thorsten
%A Granka, Laura
%A Pan, Bing
%A Hembrooke, Helene
%A Gay, Geri
%B Proceedings of the 28th annual ACM SIGIR conference
%C Salvador, Brazil
%D 2005
%I ACM
%K clickthrough,eyetracking,implicitfeedback,wwwsearch
%P 154--161
%R 10.1145/1076034.1076063
%T Accurately interpreting clickthrough data as implicit feedback
%U http://portal.acm.org/citation.cfm?id=1076063
%X 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.
%@ 1-59593-034-5
@inproceedings{joachims_accurately_2005,
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.},
added-at = {2009-03-05T08:48:51.000+0100},
address = {Salvador, Brazil},
author = {Joachims, Thorsten and Granka, Laura and Pan, Bing and Hembrooke, Helene and Gay, Geri},
biburl = {https://www.bibsonomy.org/bibtex/2816047055ce84e5e2d5e3a4dbcc39937/bcao},
booktitle = {Proceedings of the 28th annual ACM SIGIR conference},
description = {In this paper, Joachims investigate different ways to generate pairwise preference based on clickthough log. The experiments show that as interpreted as relative preference, clickthrough is consistent with explicit judgment.},
doi = {10.1145/1076034.1076063},
interhash = {050982b76855a6b1258ed0b40cb69018},
intrahash = {816047055ce84e5e2d5e3a4dbcc39937},
isbn = {1-59593-034-5},
keywords = {clickthrough,eyetracking,implicitfeedback,wwwsearch},
pages = {154--161},
publisher = {ACM},
timestamp = {2009-03-05T08:48:51.000+0100},
title = {Accurately interpreting clickthrough data as implicit feedback},
url = {http://portal.acm.org/citation.cfm?id=1076063},
year = 2005
}