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SIGIR
2008
ACM
13 years 5 months ago
A user browsing model to predict search engine click data from past observations
Search engine click logs provide an invaluable source of relevance information but this information is biased because we ignore which documents from the result list the users have...
Georges Dupret, Benjamin Piwowarski
WWW
2011
ACM
13 years 6 days ago
Characterizing search intent diversity into click models
Modeling a user’s click-through behavior in click logs is a challenging task due to the well-known position bias problem. Recent advances in click models have adopted the examin...
Botao Hu, Yuchen Zhang, Weizhu Chen, Gang Wang, Qi...
KDD
2009
ACM
210views Data Mining» more  KDD 2009»
14 years 1 days ago
Modeling and predicting user behavior in sponsored search
Implicit user feedback, including click-through and subsequent browsing behavior, is crucial for evaluating and improving the quality of results returned by search engines. Severa...
Josh Attenberg, Sandeep Pandey, Torsten Suel
KDD
2009
ACM
245views Data Mining» more  KDD 2009»
14 years 5 months ago
Mining rich session context to improve web search
User browsing information, particularly their non-search related activity, reveals important contextual information on the preferences and the intent of web users. In this paper, ...
Guangyu Zhu, Gilad Mishne
CIKM
2010
Springer
13 years 8 days ago
Predicting short-term interests using activity-based search context
A query considered in isolation offers limited information about a searcher's intent. Query context that considers pre-query activity (e.g., previous queries and page visits)...
Ryen W. White, Paul N. Bennett, Susan T. Dumais