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» Exemplar-Based Models for Word Meaning in Context
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COGSCI
2010
125views more  COGSCI 2010»
13 years 7 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
NLDB
2007
Springer
14 years 1 months ago
Four Methods for Supervised Word Sense Disambiguation
Word sense disambiguation is the task to identify the intended meaning of an ambiguous word in a certain context, one of the central problems in natural language processing. This p...
Kinga Schumacher
LREC
2008
111views Education» more  LREC 2008»
13 years 8 months ago
Modelling Word Similarity: an Evaluation of Automatic Synonymy Extraction Algorithms
Vector-based models of lexical semantics retrieve semantically related words automatically from large corpora by exploiting the property that words with a similar meaning tend to ...
Kris Heylen, Yves Peirsman, Dirk Geeraerts, Dirk S...
EMNLP
2011
12 years 7 months ago
Cross-Cutting Models of Lexical Semantics
Context-dependent word similarity can be measured over multiple cross-cutting dimensions. For example, lung and breath are similar thematically, while authoritative and superfici...
Joseph Reisinger, Raymond J. Mooney
HRI
2006
ACM
14 years 1 months ago
Using context and sensory data to learn first and second person pronouns
We present a method of grounded word learning that is powerful enough to learn the meanings of first and second person pronouns. The model uses the understood words in an utteran...
Kevin Gold, Brian Scassellati