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» Maximum Margin Ranking Algorithms for Information Retrieval
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DEXAW
2010
IEEE
196views Database» more  DEXAW 2010»
13 years 7 months ago
Direct Optimization of Evaluation Measures in Learning to Rank Using Particle Swarm
— One of the central issues in Learning to Rank (L2R) for Information Retrieval is to develop algorithms that construct ranking models by directly optimizing evaluation measures ...
Ósscar Alejo, Juan M. Fernández-Luna...
SIGIR
2008
ACM
13 years 7 months ago
Re-ranking search results using document-passage graphs
We present a novel passage-based approach to re-ranking documents in an initially retrieved list so as to improve precision at top ranks. While most work on passage-based document...
Michael Bendersky, Oren Kurland
CIKM
2009
Springer
14 years 2 months 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
CORR
2010
Springer
169views Education» more  CORR 2010»
13 years 2 months ago
Recommender Systems by means of Information Retrieval
In this paper we present a method for reformulating the Recommender Systems problem in an Information Retrieval one. In our tests we have a dataset of users who give ratings for s...
Alberto Costa, Fabio Roda
WWW
2005
ACM
14 years 8 months ago
Ranking definitions with supervised learning methods
This paper is concerned with the problem of definition search. Specifically, given a term, we are to retrieve definitional excerpts of the term and rank the extracted excerpts acc...
Jun Xu, Yunbo Cao, Hang Li, Min Zhao