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» Implicit user modeling for personalized search
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SIGIR
2009
ACM
14 years 2 months ago
Temporal collaborative filtering with adaptive neighbourhoods
Recommender Systems, based on collaborative filtering (CF), aim to accurately predict user tastes, by minimising the mean error achieved on hidden test sets of user ratings, afte...
Neal Lathia, Stephen Hailes, Licia Capra
CSCW
2006
ACM
14 years 1 months ago
Don't look stupid: avoiding pitfalls when recommending research papers
If recommenders are to help people be more productive, they need to support a wide variety of real-world information seeking tasks, such as those found when seeking research paper...
Sean M. McNee, Nishikant Kapoor, Joseph A. Konstan
CLEF
2008
Springer
13 years 9 months ago
Overview of WebCLEF 2008
We describe the WebCLEF 2008 task. Similarly to the 2007 edition of WebCLEF, the 2008 edition implements a multilingual "information synthesis" task, where, for a given t...
Valentin Jijkoun, Maarten de Rijke
CIKM
2007
Springer
14 years 1 months ago
Generalizing from relevance feedback using named entity wildcards
Traditional adaptive filtering systems learn the user’s interests in a rather simple way – words from relevant documents are favored in the query model, while words from irre...
Abhimanyu Lad, Yiming Yang
WSDM
2010
ACM
166views Data Mining» more  WSDM 2010»
14 years 5 months ago
Ranking Mechanisms in Twitter-Like Forums
We study the problem of designing a mechanism to rank items in forums by making use of the user reviews such as thumb and star ratings. We compare mechanisms where forum users rat...
Anish Das Sarma, Atish Das Sarma, Sreenivas Gollap...