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SIGIR
2005
ACM
14 years 1 months ago
Accurately interpreting clickthrough data as implicit feedback
This paper examines the reliability of implicit feedback generated from clickthrough data in WWW search. Analyzing the users’ decision process using eyetracking and comparing im...
Thorsten Joachims, Laura A. Granka, Bing Pan, Hele...
SIGIR
2006
ACM
14 years 1 months ago
Learning user interaction models for predicting web search result preferences
Evaluating user preferences of web search results is crucial for search engine development, deployment, and maintenance. We present a real-world study of modeling the behavior of ...
Eugene Agichtein, Eric Brill, Susan T. Dumais, Rob...
KDD
2004
ACM
148views Data Mining» more  KDD 2004»
14 years 7 months ago
Spying Out Accurate User Preferences for Search Engine Adaptation
Abstract. Most existing search engines employ static ranking algorithms that do not adapt to the specific needs of users. Recently, some researchers have studied the use of clickth...
Lin Deng, Wilfred Ng, Xiaoyong Chai, Dik Lun Lee
CIKM
2009
Springer
14 years 2 months ago
Exploring relevance for clicks
Mining feedback information from user click-through data is an important issue for modern Web retrieval systems in terms of architecture analysis, performance evaluation and algor...
Rongwei Cen, Yiqun Liu, Min Zhang, Bo Zhou, Liyun ...
WWW
2010
ACM
14 years 1 months ago
Beyond position bias: examining result attractiveness as a source of presentation bias in clickthrough data
Leveraging clickthrough data has become a popular approach for evaluating and optimizing information retrieval systems. Although data is plentiful, one must take care when interpr...
Yisong Yue, Rajan Patel, Hein Roehrig