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» Label Ranking Methods based on the Plackett-Luce Model
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ICDM
2003
IEEE
210views Data Mining» more  ICDM 2003»
15 years 5 months ago
CBC: Clustering Based Text Classification Requiring Minimal Labeled Data
Semi-supervised learning methods construct classifiers using both labeled and unlabeled training data samples. While unlabeled data samples can help to improve the accuracy of trai...
Hua-Jun Zeng, Xuanhui Wang, Zheng Chen, Hongjun Lu...
WSDM
2010
ACM
245views Data Mining» more  WSDM 2010»
15 years 9 months ago
Improving Quality of Training Data for Learning to Rank Using Click-Through Data
In information retrieval, relevance of documents with respect to queries is usually judged by humans, and used in evaluation and/or learning of ranking functions. Previous work ha...
Jingfang Xu, Chuanliang Chen, Gu Xu, Hang Li, Elbi...
HICSS
2006
IEEE
163views Biometrics» more  HICSS 2006»
15 years 5 months ago
Learning Ranking vs. Modeling Relevance
The classical (ad hoc) document retrieval problem has been traditionally approached through ranking according to heuristically developed functions (such as tf.idf or bm25) or gene...
Dmitri Roussinov, Weiguo Fan
CVPR
2012
IEEE
13 years 2 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
WIDM
2005
ACM
15 years 5 months ago
Web path recommendations based on page ranking and Markov models
Markov models have been widely used for modelling users' navigational behaviour in the Web graph, using the transitional probabilities between web pages, as recorded in the w...
Magdalini Eirinaki, Michalis Vazirgiannis, Dimitri...