Mathematical and Computational Analysis of Natural Language

Mathematical and Computational Analysis of Natural Language
Author: Carlos Martín Vide
Publisher: John Benjamins Publishing
Total Pages: 410
Release: 1998-01-01
Genre: Language Arts & Disciplines
ISBN: 9027215545

In the last decade, computational linguistics has produced a revival of the interest in the mathematical study of the various levels of human language. This volume contains a selection of recent research papers approaching mathematical and computational topics in natural languages, with a special attention being paid to syntax and semantics. According with their main focus, the papers are distributed into four parts: Syntax, Semantics, Natural language processing and Varia, which cover a vast range of problems. The book may be of interest to all those who intend to know which kind of mathematics is used when giving account of natural language, as well as to people working on computational issues involving human-machine interaction.

Computational Analysis and Understanding of Natural Languages: Principles, Methods and Applications

Computational Analysis and Understanding of Natural Languages: Principles, Methods and Applications
Author:
Publisher: Elsevier
Total Pages: 540
Release: 2018-08-27
Genre: Mathematics
ISBN: 0444640436

Computational Analysis and Understanding of Natural Languages: Principles, Methods and Applications, Volume 38, the latest release in this monograph that provides a cohesive and integrated exposition of these advances and associated applications, includes new chapters on Linguistics: Core Concepts and Principles, Grammars, Open-Source Libraries, Application Frameworks, Workflow Systems, Mathematical Essentials, Probability, Inference and Prediction Methods, Random Processes, Bayesian Methods, Machine Learning, Artificial Neural Networks for Natural Language Processing, Information Retrieval, Language Core Tasks, Language Understanding Applications, and more. The synergistic confluence of linguistics, statistics, big data, and high-performance computing is the underlying force for the recent and dramatic advances in analyzing and understanding natural languages, hence making this series all the more important. - Provides a thorough treatment of open-source libraries, application frameworks and workflow systems for natural language analysis and understanding - Presents new chapters on Linguistics: Core Concepts and Principles, Grammars, Open-Source Libraries, Application Frameworks, Workflow Systems, Mathematical Essentials, Probability, and more

Foundations of Computational Linguistics

Foundations of Computational Linguistics
Author: Roland Hausser
Publisher: Springer Science & Business Media
Total Pages: 541
Release: 2013-03-09
Genre: Computers
ISBN: 3662039206

The central task of future-oriented computational linguistics is the development of cognitive machines which humans can freely speak to in their natural language. This will involve the development of a functional theory of language, an objective method of verification, and a wide range of practical applications. Natural communication requires not only verbal processing, but also non-verbal perception and action. Therefore, the content of this book is organized as a theory of language for the construction of talking robots with a focus on the mechanics of natural language communication in both the listener and the speaker.

The Natural Language for Artificial Intelligence

The Natural Language for Artificial Intelligence
Author: Dioneia Motta Monte-Serrat
Publisher: Academic Press
Total Pages: 254
Release: 2021-03-28
Genre: Computers
ISBN: 0323859216

The Natural Language for Artificial Intelligence presents the biological and logical structure typical of human language in its dynamic mediating process between reality and the human mind. The book explains linguistic functioning in the dynamic process of human cognition when forming meaning. After that, an approach to artificial intelligence (AI) is outlined, which works with a more restricted concept of natural language that leads to flaws and ambiguities. Subsequently, the characteristics of natural language and patterns of how it behaves in different branches of science are revealed to indicate ways to improve the development of AI in specific fields of science. A brief description of the universal structure of language is also presented as an algorithmic model to be followed in the development of AI. Since AI aims to imitate the process of the human mind, the book shows how the cross-fertilization between natural language and AI should be done using the logical-axiomatic structure of natural language adjusted to the logical-mathematical processes of the machine. - Presents a comprehensive approach to natural language and its inherent and complex dynamics - Develops language content as the next frontier, identifying the universal structure of language as a common structure that appears in both AI and cognitive computing - Explains the standard structure present in cognition and AI, making them interchangeable - Offers examples of the application of the universal language model in image analysis and conventional language

The Oxford Handbook of Computational Linguistics

The Oxford Handbook of Computational Linguistics
Author: Ruslan Mitkov
Publisher: Oxford University Press
Total Pages: 808
Release: 2004
Genre: Computers
ISBN: 019927634X

This handbook of computational linguistics, written for academics, graduate students and researchers, provides a state-of-the-art reference to one of the most active and productive fields in linguistics.

Computational Linguistics

Computational Linguistics
Author: Nick Cercone
Publisher: Elsevier
Total Pages: 258
Release: 2014-06-20
Genre: Language Arts & Disciplines
ISBN: 1483190617

Computational Linguistics provides an overview of the variety of important research in computational linguistics in North America. This work is divided into 15 chapters and begins with a survey of the theoretical foundations and parsing strategies for natural language. The succeeding chapters deal with psychological and linguistic modeling, discourse processing analysis, text and content analysis, and natural language understanding, as well as knowledge organization, memory models, and learning. Other chapters describe the programming systems and considerations for computation linguistics. The last chapters look into the nature of natural language front-end processes to database systems. These chapters also examine the human factors interface. This book will prove useful to computing scientists, philosophers, psychologists, and linguists.

Formal Analysis for Natural Language Processing: A Handbook

Formal Analysis for Natural Language Processing: A Handbook
Author: Zhiwei Feng
Publisher: Springer
Total Pages: 0
Release: 2024-05-12
Genre: Computers
ISBN: 9789811651748

The field of natural language processing (NLP) is one of the most important and useful application areas of artificial intelligence. NLP is now rapidly evolving, as new methods and toolsets converge with an ever-expanding wealth of available data. This state-of-the-art handbook addresses all aspects of formal analysis for natural language processing. Following a review of the field’s history, it systematically introduces readers to the rule-based model, statistical model, neural network model, and pre-training model in natural language processing. At a time characterized by the steady and vigorous growth of natural language processing, this handbook provides a highly accessible introduction and much-needed reference guide to both the theory and method of NLP. It can be used for individual study, as the textbook for courses on natural language processing or computational linguistics, or as a supplement to courses on artificial intelligence, and offers a valuable asset for researchers, practitioners, lecturers, graduate and undergraduate students alike.

Methods and Models in Artificial and Natural Computation. A Homage to Professor Mira's Scientific Legacy

Methods and Models in Artificial and Natural Computation. A Homage to Professor Mira's Scientific Legacy
Author: Jose Mira
Publisher: Springer Science & Business Media
Total Pages: 550
Release: 2009-06-12
Genre: Computers
ISBN: 3642022634

The two-volume set LNCS 5601 and LNCS 5602 constitutes the refereed proceedings of the Third International Work-Conference on the Interplay between Natural and Artificial Computation, IWINAC 2009, held in Santiago de Compostela, Spain, in June 2009. The 108 revised papers presented are thematically divided into two volumes. The first volume includes papers relating the most recent collaborations with Professor Mira and contributions mainly related with theoretical, conceptual and methodological aspects linking AI and knowledge engineering with neurophysiology, clinics and cognition. The second volume contains all the contributions connected with biologically inspired methods and techniques for solving AI and knowledge engineering problems in different application domains.

Deep Learning in Natural Language Processing

Deep Learning in Natural Language Processing
Author: Li Deng
Publisher: Springer
Total Pages: 338
Release: 2018-05-23
Genre: Computers
ISBN: 9811052093

In recent years, deep learning has fundamentally changed the landscapes of a number of areas in artificial intelligence, including speech, vision, natural language, robotics, and game playing. In particular, the striking success of deep learning in a wide variety of natural language processing (NLP) applications has served as a benchmark for the advances in one of the most important tasks in artificial intelligence. This book reviews the state of the art of deep learning research and its successful applications to major NLP tasks, including speech recognition and understanding, dialogue systems, lexical analysis, parsing, knowledge graphs, machine translation, question answering, sentiment analysis, social computing, and natural language generation from images. Outlining and analyzing various research frontiers of NLP in the deep learning era, it features self-contained, comprehensive chapters written by leading researchers in the field. A glossary of technical terms and commonly used acronyms in the intersection of deep learning and NLP is also provided. The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers and industrial researchers, as well as anyone interested in deep learning and natural language processing.

Introduction to Natural Language Processing

Introduction to Natural Language Processing
Author: Jacob Eisenstein
Publisher: MIT Press
Total Pages: 536
Release: 2019-10-01
Genre: Computers
ISBN: 0262354578

A survey of computational methods for understanding, generating, and manipulating human language, which offers a synthesis of classical representations and algorithms with contemporary machine learning techniques. This textbook provides a technical perspective on natural language processing—methods for building computer software that understands, generates, and manipulates human language. It emphasizes contemporary data-driven approaches, focusing on techniques from supervised and unsupervised machine learning. The first section establishes a foundation in machine learning by building a set of tools that will be used throughout the book and applying them to word-based textual analysis. The second section introduces structured representations of language, including sequences, trees, and graphs. The third section explores different approaches to the representation and analysis of linguistic meaning, ranging from formal logic to neural word embeddings. The final section offers chapter-length treatments of three transformative applications of natural language processing: information extraction, machine translation, and text generation. End-of-chapter exercises include both paper-and-pencil analysis and software implementation. The text synthesizes and distills a broad and diverse research literature, linking contemporary machine learning techniques with the field's linguistic and computational foundations. It is suitable for use in advanced undergraduate and graduate-level courses and as a reference for software engineers and data scientists. Readers should have a background in computer programming and college-level mathematics. After mastering the material presented, students will have the technical skill to build and analyze novel natural language processing systems and to understand the latest research in the field.