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» Learning Relations Using Collocations
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EMNLP
2008
15 years 4 months ago
Phrase Translation Probabilities with ITG Priors and Smoothing as Learning Objective
The conditional phrase translation probabilities constitute the principal components of phrase-based machine translation systems. These probabilities are estimated using a heurist...
Markos Mylonakis, Khalil Sima'an
142
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WWW
2009
ACM
16 years 3 months ago
Learning to recognize reliable users and content in social media with coupled mutual reinforcement
Community Question Answering (CQA) has emerged as a popular forum for users to pose questions for other users to answer. Over the last few years, CQA portals such as Naver and Yah...
Jiang Bian, Yandong Liu, Ding Zhou, Eugene Agichte...
178
Voted
GEOS
2009
Springer
15 years 7 months ago
Bottom-Up Gazetteers: Learning from the Implicit Semantics of Geotags
As directories of named places, gazetteers link the names to geographic footprints and place types. Most existing gazetteers are managed strictly top-down: entries can only be adde...
Carsten Keßler, Patrick Maué, Jan Tor...
177
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COLT
1994
Springer
15 years 6 months ago
Bayesian Inductive Logic Programming
Inductive Logic Programming (ILP) involves the construction of first-order definite clause theories from examples and background knowledge. Unlike both traditional Machine Learnin...
Stephen Muggleton
FLAIRS
2000
15 years 4 months ago
Reasoning from Data Rather than Theory
Thecurrent frameworkfor constructing intelligent tutoring systems(ITS) is to use psychological/pedagogical theories of learning, and encode this knowledgeinto the tutor. However,t...
Joseph E. Beck, Beverly Park Woolf