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SIGIR
2006
ACM
14 years 3 months ago
Learning a ranking from pairwise preferences
We introduce a novel approach to combining rankings from multiple retrieval systems. We use a logistic regression model or an SVM to learn a ranking from pairwise document prefere...
Ben Carterette, Desislava Petkova
CIKM
2008
Springer
13 years 11 months ago
Are click-through data adequate for learning web search rankings?
Learning-to-rank algorithms, which can automatically adapt ranking functions in web search, require a large volume of training data. A traditional way of generating training examp...
Zhicheng Dou, Ruihua Song, Xiaojie Yuan, Ji-Rong W...
SEMWEB
2009
Springer
14 years 4 months ago
Towards Lightweight and Robust Large Scale Emergent Knowledge Processing
We present a lightweight framework for processing uncertain emergent knowledge that comes from multiple resources with varying relevance. The framework is essentially RDF-compatibl...
Vít Novácek, Stefan Decker
TAL
2010
Springer
13 years 8 months ago
Concept Based Representations for Ranking in Geographic Information Retrieval
Abstract. Geographic Information Retrieval (GIR) is a specialized Information Retrieval (IR) branch that deals with information related to geographical locations. Traditional IR en...
Maya Carrillo, Esaú Villatoro-Tello, Aureli...
KDD
2009
ACM
184views Data Mining» more  KDD 2009»
14 years 4 months ago
Thumbs-Up: a game for playing to rank search results
Human computation is an effective way to channel human effort spent playing games to solving computational problems that are easy for humans but difficult for computers to autom...
Ali Dasdan, Chris Drome, Santanu Kolay, Micah Alpe...