Natural Language Processing In Artificial Intelligence Nlpinai 2020
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Natural Language Processing in Artificial Intelligence—NLPinAI 2020
Author: Roussanka Loukanova
language: en
Publisher: Springer Nature
Release Date: 2021-03-25
This book covers theoretical work, applications, approaches, and techniques for computational models of information and its presentation by language (artificial, human, or natural in other ways). Computational and technological developments that incorporate natural language are proliferating. Adequate coverage encounters difficult problems related to ambiguities and dependency on context and agents (humans or computational systems). The goal is to promote computational systems of intelligent natural language processing and related models of computation, language, thought, mental states, reasoning, and other cognitive processes.
Natural Language Processing in Artificial Intelligence — NLPinAI 2021
Author: Roussanka Loukanova
language: en
Publisher: Springer Nature
Release Date: 2021-11-01
The book covers theoretical work, approaches, applications, and techniques for computational models of information, language, and reasoning. Computational and technological developments that incorporate natural language are proliferating. Adequate coverage of natural language processing in artificial intelligence encounters problems on developments of specialized computational approaches and algorithms. Many difficulties are due to ambiguities in natural language and dependency of interpretations on contexts and agents. Classical approaches proceed with relevant updates, and new developments emerge in theories of formal and natural languages, computational models of information and reasoning, and related computerized applications. Its focus is on computational processing of human language and relevant medium languages, which can be theoretically formal, or for programming and specification of computational systems. The goal is to promote intelligent natural language processing, along with models of computation, language, reasoning, and other cognitive processes.
Modelling Natural Language with Claude Shannon’s Notion of Surprisal
Author: Michael Richter
language: en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date: 2024-02-19
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.