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SIGIR
2011
ACM
12 years 11 months ago
Pseudo test collections for learning web search ranking functions
Test collections are the primary drivers of progress in information retrieval. They provide a yardstick for assessing the effectiveness of ranking functions in an automatic, rapi...
Nima Asadi, Donald Metzler, Tamer Elsayed, Jimmy L...
GECCO
2009
Springer
151views Optimization» more  GECCO 2009»
14 years 3 months ago
Swarming to rank for information retrieval
This paper presents an approach to automatically optimize the retrieval quality of ranking functions. Taking a Swarm Intelligence perspective, we present a novel method, SwarmRank...
Ernesto Diaz-Aviles, Wolfgang Nejdl, Lars Schmidt-...
IJON
2010
112views more  IJON 2010»
13 years 6 months ago
Efficient voting prediction for pairwise multilabel classification
The pairwise approach to multilabel classification reduces the problem to learning and aggregating preference predictions among the possible labels. A key problem is the need to qu...
Eneldo Loza Mencía, Sang-Hyeun Park, Johann...
SCHOLARPEDIA
2008
110views more  SCHOLARPEDIA 2008»
13 years 8 months ago
Luce's choice axiom
A geometric approach is introduced to explain phenomena that can arise with Luce's choice axiom; e.g., differences occur when determining the likelihood of a ranking by start...
Duncan Luce
NAACL
1994
13 years 10 months ago
Learning from Relevant Documents in Large Scale Routing Retrieval
The normal practice of selecting relevant documents for training routing queries is to either use all relevants or the 'best n' of them after a (retrieval) ranking opera...
K. L. Kwok, Laszlo Grunfeld