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» Learning Probabilistic Models of Word Sense Disambiguation
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EMNLP
2010
14 years 7 months ago
A New Approach to Lexical Disambiguation of Arabic Text
We describe a model for the lexical analysis of Arabic text, using the lists of alternatives supplied by a broad-coverage morphological analyzer, SAMA, which include stable lemma ...
Rushin Shah, Paramveer S. Dhillon, Mark Liberman, ...
COLING
2010
14 years 4 months ago
Bringing Active Learning to Life
Active learning has been applied to different NLP tasks, with the aim of limiting the amount of time and cost for human annotation. Most studies on active learning have only simul...
Ines Rehbein, Josef Ruppenhofer, Alexis Palmer
NIPS
2008
14 years 11 months ago
Unsupervised Learning of Visual Sense Models for Polysemous Words
Polysemy is a problem for methods that exploit image search engines to build object category models. Existing unsupervised approaches do not take word sense into consideration. We...
Kate Saenko, Trevor Darrell
GRAMMARS
2002
119views more  GRAMMARS 2002»
14 years 9 months ago
Computational Complexity of Probabilistic Disambiguation
Recent models of natural language processing employ statistical reasoning for dealing with the ambiguity of formal grammars. In this approach, statistics, concerning the various li...
Khalil Sima'an
COGSCI
2010
125views more  COGSCI 2010»
14 years 10 months ago
A Probabilistic Computational Model of Cross-Situational Word Learning
Words are the essence of communication: they are the building blocks of any language. Learning the meaning of words is thus one of the most important aspects of language acquisiti...
Afsaneh Fazly, Afra Alishahi, Suzanne Stevenson