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Bayesian natural language semantics and pragmatics [electronic resource]

Bayesian natural language semantics and pragmatics [electronic resource]

자료유형
E-Book(소장)
개인저자
Zeevat, Henk, 1952-. Schmitz, Hans-Christian.
서명 / 저자사항
Bayesian natural language semantics and pragmatics [electronic resource] / Henk Zeevat, Hans-Christian Schmitz, editors.
발행사항
Cham :   Springer International Publishing :   Imprint: Springer,   2015.  
형태사항
1 online resource (xi , 246 p.) : ill.
총서사항
Language, cognition, and mind,2364-4109, 2364-4117 (electronic) ; 2
ISBN
9783319170640
요약
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.
일반주기
Title from e-Book title page.  
내용주기
Preface by Henk Zeevat & Hans-Christian Schmitz -- 1. Perspectives on Bayesian Natural Language Semantics and Pragmatics by Henk Zeevat -- 2. Causal Bayesian Networks, Signalling Games and Implicature of `More than n' by Anton Benz -- 3. Measurement-Theoretic Foundations of Logic for Better Questions and Answers by Satoru Suzuki -- 4. Conditionals, Conditional Probabilities, and Conditionalization by Stefan Kaufmann -- 5. On the Probabilistic Notion of Causality: Models and Metalanguages by Christian Wurm -- 6. Shannon vs. Chomsky: Brain Potentials and the Syntax-Semantics Distinction by Mathias Winther Madsen -- 7. Orthogonality and Presuppositions. A Bayesian Perspective by Jacques Jayez -- 8. Layered Meanings and Bayesian Argumentation: The Case of Exclusives by Grégoire Winterstein -- 9. Variations on a Bayesian Theme: Comparing Bayesian Models of Referential Reasoning by Ciyang Qing and Michael Franke -- 10. Towards a Probabilistic Semantics for Vague Adjectives by Peter Sutton.
서지주기
Includes bibliographical references.
이용가능한 다른형태자료
Issued also as a book.  
일반주제명
Bayesian statistical decision theory. Language and languages --Study and teaching --Statistical methods.
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245 0 0 ▼a Bayesian natural language semantics and pragmatics ▼h [electronic resource] / ▼c Henk Zeevat, Hans-Christian Schmitz, editors.
260 ▼a Cham : ▼b Springer International Publishing : ▼b Imprint: Springer, ▼c 2015.
300 ▼a 1 online resource (xi , 246 p.) : ▼b ill.
490 1 ▼a Language, cognition, and mind, ▼x 2364-4109, ▼x 2364-4117 (electronic) ; ▼v 2
500 ▼a Title from e-Book title page.
504 ▼a Includes bibliographical references.
505 0 ▼a Preface by Henk Zeevat & Hans-Christian Schmitz -- 1. Perspectives on Bayesian Natural Language Semantics and Pragmatics by Henk Zeevat -- 2. Causal Bayesian Networks, Signalling Games and Implicature of `More than n' by Anton Benz -- 3. Measurement-Theoretic Foundations of Logic for Better Questions and Answers by Satoru Suzuki -- 4. Conditionals, Conditional Probabilities, and Conditionalization by Stefan Kaufmann -- 5. On the Probabilistic Notion of Causality: Models and Metalanguages by Christian Wurm -- 6. Shannon vs. Chomsky: Brain Potentials and the Syntax-Semantics Distinction by Mathias Winther Madsen -- 7. Orthogonality and Presuppositions. A Bayesian Perspective by Jacques Jayez -- 8. Layered Meanings and Bayesian Argumentation: The Case of Exclusives by Grégoire Winterstein -- 9. Variations on a Bayesian Theme: Comparing Bayesian Models of Referential Reasoning by Ciyang Qing and Michael Franke -- 10. Towards a Probabilistic Semantics for Vague Adjectives by Peter Sutton.
520 ▼a 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.
530 ▼a Issued also as a book.
538 ▼a Mode of access: World Wide Web.
650 0 ▼a Bayesian statistical decision theory.
650 0 ▼a Language and languages ▼x Study and teaching ▼x Statistical methods.
700 1 ▼a Zeevat, Henk, ▼d 1952-.
700 1 ▼a Schmitz, Hans-Christian.
830 0 ▼a Language, cognition, and mind ; ▼v 2.
856 4 0 ▼u https://oca.korea.ac.kr/link.n2s?url=http://dx.doi.org/10.1007/978-3-319-17064-0
945 ▼a KLPA
991 ▼a E-Book(소장)

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