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» Learning to rank at query-time using association rules
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IDA
2006
Springer
14 years 11 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
15 years 8 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
13 years 11 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
14 years 9 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
15 years 5 months 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