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» Parallel learning to rank for information retrieval
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RECSYS
2010
ACM
13 years 3 months ago
List-wise learning to rank with matrix factorization for collaborative filtering
A ranking approach, ListRank-MF, is proposed for collaborative filtering that combines a list-wise learning-to-rank algorithm with matrix factorization (MF). A ranked list of item...
Yue Shi, Martha Larson, Alan Hanjalic
ECML
2006
Springer
13 years 9 months ago
Cost-Sensitive Learning of SVM for Ranking
Abstract. In this paper, we propose a new method for learning to rank. `Ranking SVM' is a method for performing the task. It formulizes the problem as that of binary classific...
Jun Xu, Yunbo Cao, Hang Li, Yalou Huang
SIGIR
2008
ACM
13 years 5 months ago
Learning to rank with partially-labeled data
Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...
Kevin Duh, Katrin Kirchhoff
ECML
2007
Springer
13 years 11 months ago
An Unsupervised Learning Algorithm for Rank Aggregation
Many applications in information retrieval, natural language processing, data mining, and related fields require a ranking of instances with respect to a specified criteria as op...
Alexandre Klementiev, Dan Roth, Kevin Small