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» Pairwise Preference Learning and Ranking
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AIRS
2010
Springer
13 years 9 months ago
Learning to Rank with Supplementary Data
This paper is concerned with a new task of ranking, referred to as "supplementary data assisted ranking", or "supplementary ranking" for short. Different from c...
Wenkui Ding, Tao Qin, Xu-Dong Zhang
CIKM
2008
Springer
14 years 26 days ago
Are click-through data adequate for learning web search rankings?
Learning-to-rank algorithms, which can automatically adapt ranking functions in web search, require a large volume of training data. A traditional way of generating training examp...
Zhicheng Dou, Ruihua Song, Xiaojie Yuan, Ji-Rong W...
ICML
2007
IEEE
14 years 11 months ago
Learning to rank: from pairwise approach to listwise approach
The paper is concerned with learning to rank, which is to construct a model or a function for ranking objects. Learning to rank is useful for document retrieval, collaborative fil...
Zhe Cao, Tao Qin, Tie-Yan Liu, Ming-Feng Tsai, Han...
EOR
2008
99views more  EOR 2008»
13 years 11 months ago
Ordinal regression revisited: Multiple criteria ranking using a set of additive value functions
We present a new method, called UTAGMS , for multiple criteria ranking of alternatives from set A using a set of additive value functions which result from an ordinal regression. ...
Salvatore Greco, Vincent Mousseau, Roman Slowinski
ICML
2009
IEEE
14 years 11 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