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Titlebook: Bayesian Natural Language Semantics and Pragmatics; Henk Zeevat,Hans-Christian Schmitz Book 2015 Springer International Publishing Switzer

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发表于 2025-3-21 18:07:04 | 显示全部楼层 |阅读模式
期刊全称Bayesian Natural Language Semantics and Pragmatics
影响因子2023Henk Zeevat,Hans-Christian Schmitz
视频video
发行地址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 interpr
学科分类Language, Cognition, and Mind
图书封面Titlebook: Bayesian Natural Language Semantics and Pragmatics;  Henk Zeevat,Hans-Christian Schmitz Book 2015 Springer International Publishing Switzer
影响因子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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On the Probabilistic Notion of Causality: Models and Metalanguages,heory, in particular focussing on the questions: which properties of probability spaces can be axiomatized by formulas of the new languages, and which not? In particular, we can show that desirable properties of expressive power come at the cost of counterintuitive features.
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Layered Meanings and Bayesian Argumentation: The Case of Exclusives,umentative interpretation. I support my claim by focusing on the case of the adverb . and by presenting the results of experiments which show that utterances that have similar informational contents do not behave the same way when they are argumentatively evaluated.
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https://doi.org/10.1007/978-1-4614-4205-9themselves. What is lacking is a straightforward integration of this approach in a larger framework of belief representation and dynamics. This paper discusses some of the issues involved and proposes an account of belief update by conditionalization.
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Lassad Ben Ammar,Adel Mahfoudhi statistical in nature. I show that a proper application of Shannon’s concepts to the reading process provides an interesting reinterpretation of our notion of “syntax,” thus questioning some fundamental assumptions of linguistics.
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Avi Parush,Debi Parush,Roy Ilanerged. It seems that this distinction correlates with an intuition of (non-)., that is, of (non-)independence between the main content and the presupposition. I argue that this intuition is correct to some extent but has to be clarified. To this aim, I propose a Bayesian approach, which provides a more precise rendering of orthogonality.
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https://doi.org/10.1007/978-3-031-01602-8 terms of their ability to predict relevant empirical data. The result suggests that the RSA model could be adapted and extended to improve its predictive power, in particular by taking speaker preferences into account.
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