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» Learning to rank at query-time using association rules
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IDA
2006
Springer
13 years 7 months ago
Backward chaining rule induction
Exploring the vast number of possible feature interactions in domains such as gene expression microarray data is an onerous task. We describe Backward-Chaining Rule Induction (BCR...
Douglas H. Fisher, Mary E. Edgerton, Zhihua Chen, ...
ALT
2008
Springer
14 years 4 months ago
Active Learning in Multi-armed Bandits
In this paper we consider the problem of actively learning the mean values of distributions associated with a finite number of options (arms). The algorithms can select which opti...
András Antos, Varun Grover, Csaba Szepesv&a...
EMNLP
2011
12 years 7 months ago
Random Walk Inference and Learning in A Large Scale Knowledge Base
We consider the problem of performing learning and inference in a large scale knowledge base containing imperfect knowledge with incomplete coverage. We show that a soft inference...
Ni Lao, Tom M. Mitchell, William W. Cohen
ICMLA
2009
13 years 5 months ago
All-Monotony: A Generalization of the All-Confidence Antimonotony
Abstract--Many studies have shown the limits of support/confidence framework used in Apriori-like algorithms to mine association rules. One solution to cope with this limitation is...
Yannick Le Bras, Philippe Lenca, Sorin Moga, St&ea...
WEBI
2004
Springer
14 years 28 days ago
Adaptation and Personalization in Web-based Learning Support Systems
In order to achieve optimal efficiency in a learning process, individual learner needs his/her own personalized assistance. For a web-based open and dynamic learning environment, ...
Lisa Fan