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» Maximum Margin Ranking Algorithms for Information Retrieval
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CIKM
2005
Springer
13 years 9 months ago
Using RankBoost to compare retrieval systems
This paper presents a new pooling method for constructing the assessment sets used in the evaluation of retrieval systems. Our proposal is based on RankBoost, a machine learning v...
Huyen-Trang Vu, Patrick Gallinari
SIGECOM
2005
ACM
93views ECommerce» more  SIGECOM 2005»
14 years 1 months ago
Ranking systems: the PageRank axioms
This paper initiates research on the foundations of ranking systems, a fundamental ingredient of basic e-commerce and Internet Technologies. In order to understand the essence and...
Alon Altman, Moshe Tennenholtz
ICMLA
2009
13 years 5 months ago
Structured Prediction with Relative Margin
In structured prediction problems, outputs are not confined to binary labels; they are often complex objects such as sequences, trees, or alignments. Support Vector Machine (SVM) ...
Pannagadatta K. Shivaswamy, Tony Jebara
CLEF
2006
Springer
13 years 11 months ago
A High Precision Information Retrieval Method for WiQA
This paper presents Wolverhampton University's participation in the WiQA competition. The method chosen for this task combines a high precision, but low recall information re...
Constantin Orasan, Georgiana Puscasu
SIGIR
2011
ACM
12 years 10 months ago
Utilizing marginal net utility for recommendation in e-commerce
Traditional recommendation algorithms often select products with the highest predicted ratings to recommend. However, earlier research in economics and marketing indicates that a ...
Jian Wang, Yi Zhang