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» Ranking functions and rankings on languages
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CVPR
2012
IEEE
11 years 10 months ago
Robust late fusion with rank minimization
In this paper, we propose a rank minimization method to fuse the predicted confidence scores of multiple models, each of which is obtained based on a certain kind of feature. Spe...
Guangnan Ye, Dong Liu, I-Hong Jhuo, Shih-Fu Chang
ICDE
2009
IEEE
194views Database» more  ICDE 2009»
14 years 9 months ago
Effective XML Keyword Search with Relevance Oriented Ranking
Abstract-- Inspired by the great success of information retrieval (IR) style keyword search on the web, keyword search on XML has emerged recently. The difference between text data...
Zhifeng Bao, Tok Wang Ling, Bo Chen, Jiaheng Lu
WSDM
2012
ACM
267views Data Mining» more  WSDM 2012»
12 years 3 months ago
Learning to rank with multi-aspect relevance for vertical search
Many vertical search tasks such as local search focus on specific domains. The meaning of relevance in these verticals is domain-specific and usually consists of multiple well-d...
Changsung Kang, Xuanhui Wang, Yi Chang, Belle L. T...
CIKM
2009
Springer
14 years 2 months ago
Feature selection for ranking using boosted trees
Modern search engines have to be fast to satisfy users, so there are hard back-end latency requirements. The set of features useful for search ranking functions, though, continues...
Feng Pan, Tim Converse, David Ahn, Franco Salvetti...
ESSMAC
2003
Springer
14 years 27 days ago
Analysis of Some Methods for Reduced Rank Gaussian Process Regression
Abstract. While there is strong motivation for using Gaussian Processes (GPs) due to their excellent performance in regression and classification problems, their computational com...
Joaquin Quiñonero Candela, Carl Edward Rasm...