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Modelling Natural Language with Claude Shannon's Notion of Surprisal.

De Gruyter DG Plus DeG Package 2024 Part 1 Available online

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Format:
Book
Author/Creator:
Richter, Michael.
Series:
Quantitative Linguistics [QL] Series
Quantitative Linguistics [QL] Series ; v.76
Language:
English
Physical Description:
1 online resource (192 pages)
Edition:
1st ed.
Place of Publication:
Basel/Berlin/Boston : De Gruyter, Inc., 2024.
Summary:
Have you ever wondered how the principles behind Shannon's groundbreaking Information Theory can be interwoven with the intricate fabric of linguistic communication? This book takes you on a fascinating journey, offering insights into how humans process and comprehend language. By applying Information Theory to the realm of natural language semantics, it unravels the connection between regularities in linguistic messages and the cognitive intricacies of language processing. Highlighting the intersections of information theory with linguistics, philosophy, cognitive psychology, and computer science, this book serves as an inspiration for anyone seeking to understand the predictive capabilities of Information Theory in modeling human communication. It elaborates on the seminal works from giants in the field like Dretske, Hale, and Zipf, exploring concepts like surprisal theory and the principle of least effort. With its empirical approach, this book not only discusses the theoretical aspects but also ventures into the application of Shannon's Information Theory in real-world language scenarios, strengthened by advanced statistical methods and machine learning. It touches upon challenging areas such as the distinction between mathematical and semantic information, the concept of information in linguistic utterances, and the intricate play between truth, context, and meaning. Whether you are a linguist, a cognitive psychologist, a philosopher, or simply an enthusiast eager to dive deep into the world where language meets information, this book promises a thought-provoking journey.
Contents:
Intro
Acknowledgements
List of figures
List of tables
Introduction
Chapter 1 Information and contexts
Chapter 2 Previous work on application of Information Theory to the semantics of natural language
Chapter 3 Modelling intensification through Shannon information
Chapter 4 Shannon Information in information retrieval
Chapter 5 Shannon information, form and linguistic coding
Chapter 6 Some concluding remarks
References
Index.
Notes:
Description based on publisher supplied metadata and other sources.
ISBN:
9783110788143
3110788144
OCLC:
1418731174

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