Hans-Christian Schmitz – författare

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.

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.

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.

This book constitutes the proceedings of the International Workshop on Vagueness in Communication, VIC 2009, held as part of ESSLLI 2009, in Bordeaux, France, July 20-24, 2009.The 11 contributions presented shed a light on new aspects in the area of vagueness in natural language communication. In contrast to the classical instruments of dealing with vagueness - like multi-valued logics, truth value gaps or gluts, or supervaluations - this volume presents new approaches like context-sensitivity of vagueness, the sharpening of vague predicates in context, and the modeling of precision levels.

This book constitutes the proceedings of the International Workshop on Vagueness in Communication, VIC 2009, held as part of ESSLLI 2009, in Bordeaux, France, July 20-24, 2009.The 11 contributions presented shed a light on new aspects in the area of vagueness in natural language communication. In contrast to the classical instruments of dealing with vagueness - like multi-valued logics, truth value gaps or gluts, or supervaluations - this volume presents new approaches like context-sensitivity of vagueness, the sharpening of vague predicates in context, and the modeling of precision levels.