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MTA
2006
173views more  MTA 2006»
15 years 3 months ago
Active learning in very large databases
Abstract. Query-by-example and query-by-keyword both suffer from the problem of "aliasing," meaning that example-images and keywords potentially have variable interpretat...
Navneet Panda, Kingshy Goh, Edward Y. Chang
NPL
2006
90views more  NPL 2006»
15 years 3 months ago
Hierarchical Incremental Class Learning with Reduced Pattern Training
Hierarchical Incremental Class Learning (HICL) is a new task decomposition method that addresses the pattern classification problem. HICL is proven to be a good classifier but clos...
Sheng Uei Guan, Chunyu Bao, Ru-Tian Sun
IJIM
2007
174views more  IJIM 2007»
15 years 3 months ago
Contextual Mobile Learning: A Step Further to Mastering Professional Appliances
—In this paper we describe our approach whose objective is to apply MOCOCO concepts to e-learning. After a short presentation of MOCOCO (Mobility, COoperation, Contextua-lisation...
Bertrand T. David, René Chalon, Olivier Cha...
134
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DIS
2010
Springer
15 years 1 months ago
Speeding Up and Boosting Diverse Density Learning
Abstract. In multi-instance learning, each example is described by a bag of instances instead of a single feature vector. In this paper, we revisit the idea of performing multi-ins...
James R. Foulds, Eibe Frank
ACL
2009
15 years 1 months ago
Learning foci for Question Answering over Topic Maps
This paper introduces the concepts of asking point and expected answer type as variations of the question focus. They are of particular importance for QA over semistructured data,...
Alexander Mikhailian, Tiphaine Dalmas, Rani Pinchu...