Bayesian Natural Language Semantics and Pragmatics
Editors: Zeevat, Henk, Schmitz, Hans-Christian (Eds.)
- The first volume on a highly promising approach to Natural Language Interpretation that fits with the use of stochastic methods
- Offers a solid introduction and in-depth exploration of Bayesian interpretation of Natural Language semantics
- Introduces new applications to argumentation and adjective semantics
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- About this book
-
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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Bibliographic Information
- Bibliographic Information
-
- Book Title
- Bayesian Natural Language Semantics and Pragmatics
- Editors
-
- Henk Zeevat
- Hans-Christian Schmitz
- Series Title
- Language, Cognition, and Mind
- Series Volume
- 2
- Copyright
- 2015
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer International Publishing Switzerland
- eBook ISBN
- 978-3-319-17064-0
- DOI
- 10.1007/978-3-319-17064-0
- Hardcover ISBN
- 978-3-319-17063-3
- Softcover ISBN
- 978-3-319-38625-6
- Series ISSN
- 2364-4109
- Edition Number
- 1
- Number of Pages
- XI, 246
- Number of Illustrations and Tables
- 29 b/w illustrations
- Topics
