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ACL
2006
15 years 5 months ago
On2L - A Framework for Incremental Ontology Learning in Spoken Dialog Systems
An open-domain spoken dialog system has to deal with the challenge of lacking lexical as well as conceptual knowledge. As the real world is constantly changing, it is not possible...
Berenike Loos
149
Voted
IJAR
2010
152views more  IJAR 2010»
15 years 2 months ago
Structural-EM for learning PDG models from incomplete data
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
Jens D. Nielsen, Rafael Rumí, Antonio Salme...
JMLR
2011
187views more  JMLR 2011»
14 years 10 months ago
Exploitation of Machine Learning Techniques in Modelling Phrase Movements for Machine Translation
We propose a distance phrase reordering model (DPR) for statistical machine translation (SMT), where the aim is to learn the grammatical rules and context dependent changes using ...
Yizhao Ni, Craig Saunders, Sándor Szedm&aac...
CVPR
2010
IEEE
16 years 4 days ago
Tracking the Invisible: Learning Where the Object Might be
Objects are usually embedded into context. Visual context has been successfully used in object detection tasks, however, it is often ignored in object tracking. We propose a metho...
Helmut Grabner, Jiri Matas, Philippe Cattin, Luc V...
115
Voted
CSIE
2009
IEEE
15 years 10 months ago
Automatic Preposition Errors Correction Using Inductive Learning
In this paper, we describe a system for correcting English preposition errors automatically. Non-native English writers often make these errors. Our system uses rules extracted au...
Hokuto Ototake, Kenji Araki