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» Recent advances in ranking and selection
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CEC
2007
IEEE
13 years 9 months ago
Ranking-Dominance and Many-Objective Optimization
An alternative relation to Pareto-dominance is studied. The relation is based on ranking a set of solutions according to each separate objective and an aggregation function to calc...
Saku Kukkonen, Jouni Lampinen
ICDE
2008
IEEE
189views Database» more  ICDE 2008»
13 years 11 months ago
Adapting ranking functions to user preference
— Learning to rank has become a popular method for web search ranking. Traditionally, expert-judged examples are the major training resource for machine learned web ranking, whic...
Keke Chen, Ya Zhang, Zhaohui Zheng, Hongyuan Zha, ...
CIKM
2009
Springer
13 years 8 months ago
Efficient feature weighting methods for ranking
Feature weighting or selection is a crucial process to identify an important subset of features from a data set. Removing irrelevant or redundant features can improve the generali...
Hwanjo Yu, Jinoh Oh, Wook-Shin Han
ECIR
2003
Springer
13 years 6 months ago
From Uncertain Inference to Probability of Relevance for Advanced IR Applications
Uncertain inference is a probabilistic generalisation of the logical view on databases, ranking documents according to their probabilities that they logically imply the query. For ...
Henrik Nottelmann, Norbert Fuhr
WWW
2005
ACM
14 years 5 months ago
TotalRank: ranking without damping
PageRank is defined as the stationary state of a Markov chain obtained by perturbing the transition matrix of a web graph with a damping factor that spreads part of the rank. The...
Paolo Boldi