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» Adapting ranking SVM to document retrieval
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SIGIR
2006
ACM
13 years 10 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...
WWW
2005
ACM
14 years 5 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
ECML
2006
Springer
13 years 8 months ago
Cost-Sensitive Learning of SVM for Ranking
Abstract. In this paper, we propose a new method for learning to rank. `Ranking SVM' is a method for performing the task. It formulizes the problem as that of binary classific...
Jun Xu, Yunbo Cao, Hang Li, Yalou Huang
SIGIR
2009
ACM
13 years 11 months ago
A ranking approach to keyphrase extraction
This paper addresses the issue of automatically extracting keyphrases from document. Previously, this problem was formalized as classification and learning methods for classific...
Xin Jiang, Yunhua Hu, Hang Li
ECIR
2009
Springer
14 years 1 months ago
Active Sampling for Rank Learning via Optimizing the Area under the ROC Curve
Abstract. Learning ranking functions is crucial for solving many problems, ranging from document retrieval to building recommendation systems based on an individual user’s prefer...
Pinar Donmez, Jaime G. Carbonell