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» Learning to rank on graphs
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KDD
2007
ACM
178views Data Mining» more  KDD 2007»
16 years 6 months ago
Real-time ranking with concept drift using expert advice
In many practical applications, one is interested in generating a ranked list of items using information mined from continuous streams of data. For example, in the context of comp...
Hila Becker, Marta Arias
BIOCOMP
2007
15 years 7 months ago
Learning Node Replacement Graph Grammars in Metabolic Pathways
— This paper describes graph-based relational, unsupervised learning algorithm to infer node replacement graph grammar and its application to metabolic pathways. We search for fr...
Jacek P. Kukluk, Chang Hun You, Lawrence B. Holder...
CIKM
2009
Springer
16 years 23 days ago
On domain similarity and effectiveness of adapting-to-rank
Adapting to rank address the the problem of insufficient domainspecific labeled training data in learning to rank. However, the initial study shows that adaptation is not always...
Keke Chen, Jing Bai, Srihari Reddy, Belle L. Tseng
ISBRA
2011
Springer
14 years 9 months ago
Query-Adaptive Ranking with Support Vector Machines for Protein Homology Prediction
Abstract. Protein homology prediction is a crucial step in templatebased protein structure prediction. The functions that rank the proteins in a database according to their homolog...
Yan Fu, Rong Pan, Qiang Yang, Wen Gao
SIGIR
2012
ACM
13 years 8 months ago
Robust ranking models via risk-sensitive optimization
Many techniques for improving search result quality have been proposed. Typically, these techniques increase average effectiveness by devising advanced ranking features and/or by...
Lidan Wang, Paul N. Bennett, Kevyn Collins-Thompso...