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» Learning to Select a Ranking Function
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GECCO
2008
Springer
145views Optimization» more  GECCO 2008»
13 years 9 months ago
Threshold selecting: best possible probability distribution for crossover selection in genetic algorithms
The paper considers the problem of selecting individuals in the current population in Genetic Algorithms for crossover to find a solution of high fitness of a given combinatoria...
Jörg Lässig, Karl Heinz Hoffmann, Mihael...
AIRS
2010
Springer
13 years 6 months ago
Relevance Ranking Using Kernels
This paper is concerned with relevance ranking in search, particularly that using term dependency information. It proposes a novel and unified approach to relevance ranking using ...
Jun Xu, Hang Li, Chaoliang Zhong
COLING
2010
13 years 2 months ago
Cross-Market Model Adaptation with Pairwise Preference Data for Web Search Ranking
Machine-learned ranking techniques automatically learn a complex document ranking function given training data. These techniques have demonstrated the effectiveness and flexibilit...
Jing Bai, Fernando Diaz, Yi Chang, Zhaohui Zheng, ...
COLING
2008
13 years 9 months ago
Rank Distance as a Stylistic Similarity
In this paper we propose a new distance function (rank distance) designed to reflect stylistic similarity between texts. To assess the ability of this distance measure to capture ...
Marius Popescu, Liviu Petrisor Dinu
CIKM
2008
Springer
13 years 10 months ago
Suppressing outliers in pairwise preference ranking
Many of the recently proposed algorithms for learning feature-based ranking functions are based on the pairwise preference framework, in which instead of taking documents in isola...
Vitor R. Carvalho, Jonathan L. Elsas, William W. C...