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Bayesian natural language semantics and pragmatics

Author: Henk Zeevat; Hans-Christian Schmitz
Publisher: Cham : Springer, [2015] ©2015
Series: Language, cognition, and mind, volume 2
Edition/Format:   Print book : EnglishView all editions and formats
Database:WorldCat
Summary:
The contributions in this volume focus on the Bayesian interpretation of natural languages, which is widely used in areas of artificial intelligence, cognitive science, and computational linguistics. This is the first volume to take up topics in Bayesian Natural Language Interpretation and make proposals based on information theory, probability theory, and related fields. The methodologies offered here extend to the  Read more...
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Document Type: Book
All Authors / Contributors: Henk Zeevat; Hans-Christian Schmitz
ISBN: 3319170635 9783319170633
OCLC Number: 904459921
Description: xi, 246 pages : illustrations ; 24 cm.
Contents: Perspectives on Bayesian natural language semantics and pragmatics / Henk Zeevat --
Causal Bayesian networks, signalling games and implicature of 'More than n' / Anton Benz --
Measurement-theoretic foundations of logic for better questions and answers / Satoru Suzuki --
Conditionals, conditional probabilites, and conditionalization / Stefan Kaufmann --
On the probabilistic notion of casuality : models and metalanguages / Christian Wurm --
Shannon versus Chomsky : brain potentials and the syntax-semantics distinction / Mathias Winther Madsen --
Orthogonality and presuppositions : a Bayesian perspective / Jacques Jayez --
Layered meanings and Bayesian argumentation : the case of exclusives / Grégoire Winterstein --
Variations on a Bayesian theme : comparing Bayesian models of referential reasoning / Ciyang Quing and Michael Franke --
Towards a probabilistic semantics for vague adjectives / Peter R. Sutton.
Series Title: Language, cognition, and mind, volume 2
Responsibility: Henk Zeevat, Hans-Christian Schmitz, editors.
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Abstract:

The contributions in this volume focus on the Bayesian interpretation of natural languages, which is widely used in areas of artificial intelligence, cognitive science, and computational linguistics. This is the first volume to take up topics in Bayesian Natural Language Interpretation and make proposals based on information theory, probability theory, and related fields. The methodologies offered here extend to the target semantic and pragmatic analyses of computational natural language interpretation. Bayesian approaches to natural language semantics and pragmatics are based on methods from signal processing and the causal Bayesian models pioneered by especially Pearl. In signal processing, the Bayesian method finds the most probable interpretation by finding the one that maximizes the product of the prior probability and the likelihood of the interpretation. It thus stresses the importance of a production model for interpretation as in Grice's contributions to pragmatics or in interpretation by abduction.

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