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» Implicit user modeling for personalized search
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KDD
2005
ACM
218views Data Mining» more  KDD 2005»
14 years 8 months ago
A maximum entropy web recommendation system: combining collaborative and content features
Web users display their preferences implicitly by navigating through a sequence of pages or by providing numeric ratings to some items. Web usage mining techniques are used to ext...
Xin Jin, Yanzan Zhou, Bamshad Mobasher
CHI
2009
ACM
13 years 11 months ago
Connecting the dots with related notes
During visual analysis, users must often connect insights discovered at various points of time to understand implicit relations within their analysis. This process is often called...
Yedendra Babu Shrinivasan, David Gotz
CIKM
2008
Springer
13 years 9 months ago
Modeling multi-step relevance propagation for expert finding
An expert finding system allows a user to type a simple text query and retrieve names and contact information of individuals that possess the expertise expressed in the query. Thi...
Pavel Serdyukov, Henning Rode, Djoerd Hiemstra
ECIR
2009
Springer
14 years 4 months ago
Classifying and Characterizing Query Intent
Understanding the intent underlying user queries may help personalize search results and improve user satisfaction. In this paper, we develop a methodology for using ad clickthroug...
Azin Ashkan, Charles L. A. Clarke, Eugene Agichtei...
TKDD
2010
121views more  TKDD 2010»
13 years 6 months ago
Factor in the neighbors: Scalable and accurate collaborative filtering
Recommender systems provide users with personalized suggestions for products or services. These systems often rely on Collaborating Filtering (CF), where past transactions are ana...
Yehuda Koren