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» Learning to rank for information retrieval
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SIGIR
2006
ACM
14 years 1 months ago
Adapting ranking SVM to document retrieval
The paper is concerned with applying learning to rank to document retrieval. Ranking SVM is a typical method of learning to rank. We point out that there are two factors one must ...
Yunbo Cao, Jun Xu, Tie-Yan Liu, Hang Li, Yalou Hua...
SIGIR
2012
ACM
11 years 10 months ago
Top-k learning to rank: labeling, ranking and evaluation
In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
Shuzi Niu, Jiafeng Guo, Yanyan Lan, Xueqi Cheng
WWW
2006
ACM
14 years 8 months ago
Beyond PageRank: machine learning for static ranking
Since the publication of Brin and Page's paper on PageRank, many in the Web community have depended on PageRank for the static (query-independent) ordering of Web pages. We s...
Matthew Richardson, Amit Prakash, Eric Brill
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...
ICML
2009
IEEE
14 years 8 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