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JIB
2010
113views more  JIB 2010»
13 years 2 months ago
The LAILAPS Search Engine: Relevance Ranking in Life Science Databases
Matthias Lange, Karl Spies, Joachim Bargsten, Greg...
ICML
2009
IEEE
14 years 8 months ago
BoltzRank: learning to maximize expected ranking gain
Ranking a set of retrieved documents according to their relevance to a query is a popular problem in information retrieval. Methods that learn ranking functions are difficult to o...
Maksims Volkovs, Richard S. Zemel
CW
2005
IEEE
14 years 1 months ago
ComRank: Metasearch and Automatic Ranking of XML Retrieval System
Different information retrieval (IR) systems often return very diverse results lists for the same query. This is problematic for users since no one IR system works best for every ...
Alan Woodley, Shlomo Geva
ICML
2002
IEEE
14 years 8 months ago
Cranking: Combining Rankings Using Conditional Probability Models on Permutations
A new approach to ensemble learning is introduced that takes ranking rather than classification as fundamental, leading to models on the symmetric group and its cosets. The approa...
Guy Lebanon, John D. Lafferty
JMLR
2010
118views more  JMLR 2010»
13 years 2 months ago
Learning to Rank for Personalized News Article Retrieval
This paper aims to tackle the very interesting and important problem of user personalized ranking of search results. The focus is on news retrieval and the data from which the ran...
Lorand Dali, Blaz Fortuna, Jan Rupnik