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COGSCI
2002

Statistical models for the induction and use of selectional preferences

8 years 11 months ago
Statistical models for the induction and use of selectional preferences
Selectional preferences have a long history in both generative and computational linguistics. However, since the publication of Resnik's dissertation in 1993, a new approach has surfaced in the computational linguistics community. This new line of research combines knowledge represented in a pre-defined semantic class hierarchy with statistical tools including information theory, statistical modeling, and Bayesian inference. These tools are used to learn selectional preferences from examples in a corpus. Instead of simple sets of semantic classes, selectional preferences are viewed as probability distributions over various entities. We survey research that extends Resnik's initial work, discuss the strengths and weaknesses of each approach, and show how they together form a cohesive line of research.
Marc Light, Warren R. Greiff
Added 17 Dec 2010
Updated 17 Dec 2010
Type Journal
Year 2002
Where COGSCI
Authors Marc Light, Warren R. Greiff
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