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» Reciprocal rank fusion outperforms condorcet and individual ...
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SIGIR
2009
ACM
13 years 11 months ago
Reciprocal rank fusion outperforms condorcet and individual rank learning methods
Reciprocal Rank Fusion (RRF), a simple method for combining the document rankings from multiple IR systems, consistently yields better results than any individual system, and bett...
Gordon V. Cormack, Charles L. A. Clarke, Stefan B&...
ICIP
2010
IEEE
13 years 2 months ago
Palmprint recognition using rank level fusion
This paper investigates a new approach for the personal recognition using rank level combination of multiple palmprint representations. There has been very little effort to study r...
Ajay Kumar, Sumit Shekhar
ICML
2009
IEEE
14 years 5 months ago
BoltzRank: learning to maximize expected ranking gain
Ranking a set of retrieved documents according to their relevance to a query is a popular problem in information retrieval. Methods that learn ranking functions are difficult to o...
Maksims Volkovs, Richard S. Zemel
CIVR
2008
Springer
245views Image Analysis» more  CIVR 2008»
13 years 6 months ago
Probabilistic optimized ranking for multimedia semantic concept detection via RVM
We present a probabilistic ranking-driven classifier for the detection of video semantic concept, such as airplane, building, etc. Most existing concept detection systems utilize ...
Yantao Zheng, Shi-Yong Neo, Tat-Seng Chua, Qi Tian
ECIR
2010
Springer
13 years 6 months ago
Learning to Select a Ranking Function
Abstract. Learning To Rank (LTR) techniques aim to learn an effective document ranking function by combining several document features. While the function learned may be uniformly ...
Jie Peng, Craig Macdonald, Iadh Ounis