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Representation and Inference for Natural Language

Author: Patrick Blackburn

Publisher: Center for the Study of Language and Information Publica Tion

Published: 2005

Total Pages: 0

ISBN-13: 9781575864969

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How can computers distinguish the coherent from the unintelligible, recognize new information in a sentence, or draw inferences from a natural language passage? Computational semantics is an exciting new field that seeks answers to these questions, and this volume is the first textbook wholly devoted to this growing subdiscipline. The book explains the underlying theoretical issues and fundamental techniques for computing semantic representations for fragments of natural language. This volume will be an essential text for computer scientists, linguists, and anyone interested in the development of computational semantics.

Book Synopsis Representation and Inference for Natural Language by : Patrick Blackburn

Download or read book Representation and Inference for Natural Language written by Patrick Blackburn and published by Center for the Study of Language and Information Publica Tion. This book was released on 2005 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can computers distinguish the coherent from the unintelligible, recognize new information in a sentence, or draw inferences from a natural language passage? Computational semantics is an exciting new field that seeks answers to these questions, and this volume is the first textbook wholly devoted to this growing subdiscipline. The book explains the underlying theoretical issues and fundamental techniques for computing semantic representations for fragments of natural language. This volume will be an essential text for computer scientists, linguists, and anyone interested in the development of computational semantics.

Representation and Inference for Natural Language

Author: Patrick Blackburn

Publisher:

Published: 1998

Total Pages: 370

ISBN-13:

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Book Synopsis Representation and Inference for Natural Language by : Patrick Blackburn

Download or read book Representation and Inference for Natural Language written by Patrick Blackburn and published by . This book was released on 1998 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Representation Learning for Natural Language Processing

Author: Zhiyuan Liu

Publisher: Springer Nature

Published: 2020-07-03

Total Pages: 319

ISBN-13: 9811555737

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This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.

Book Synopsis Representation Learning for Natural Language Processing by : Zhiyuan Liu

Download or read book Representation Learning for Natural Language Processing written by Zhiyuan Liu and published by Springer Nature. This book was released on 2020-07-03 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.

Embeddings in Natural Language Processing

Author: Mohammad Taher Pilehvar

Publisher: Morgan & Claypool Publishers

Published: 2020-11-13

Total Pages: 177

ISBN-13: 1636390226

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Embeddings have undoubtedly been one of the most influential research areas in Natural Language Processing (NLP). Encoding information into a low-dimensional vector representation, which is easily integrable in modern machine learning models, has played a central role in the development of NLP. Embedding techniques initially focused on words, but the attention soon started to shift to other forms: from graph structures, such as knowledge bases, to other types of textual content, such as sentences and documents. This book provides a high-level synthesis of the main embedding techniques in NLP, in the broad sense. The book starts by explaining conventional word vector space models and word embeddings (e.g., Word2Vec and GloVe) and then moves to other types of embeddings, such as word sense, sentence and document, and graph embeddings. The book also provides an overview of recent developments in contextualized representations (e.g., ELMo and BERT) and explains their potential in NLP. Throughout the book, the reader can find both essential information for understanding a certain topic from scratch and a broad overview of the most successful techniques developed in the literature.

Book Synopsis Embeddings in Natural Language Processing by : Mohammad Taher Pilehvar

Download or read book Embeddings in Natural Language Processing written by Mohammad Taher Pilehvar and published by Morgan & Claypool Publishers. This book was released on 2020-11-13 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: Embeddings have undoubtedly been one of the most influential research areas in Natural Language Processing (NLP). Encoding information into a low-dimensional vector representation, which is easily integrable in modern machine learning models, has played a central role in the development of NLP. Embedding techniques initially focused on words, but the attention soon started to shift to other forms: from graph structures, such as knowledge bases, to other types of textual content, such as sentences and documents. This book provides a high-level synthesis of the main embedding techniques in NLP, in the broad sense. The book starts by explaining conventional word vector space models and word embeddings (e.g., Word2Vec and GloVe) and then moves to other types of embeddings, such as word sense, sentence and document, and graph embeddings. The book also provides an overview of recent developments in contextualized representations (e.g., ELMo and BERT) and explains their potential in NLP. Throughout the book, the reader can find both essential information for understanding a certain topic from scratch and a broad overview of the most successful techniques developed in the literature.

Natural Language Processing and Knowledge Representation

Author: Łucja M. Iwańska

Publisher: AAAI Press

Published: 2000-06-19

Total Pages: 490

ISBN-13:

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"Traditionally, knowledge representation and reasoning systems have incorporated natural language as interfaces to expert systems or knowledge bases that performed tasks separate from natural language processing. As this book shows, however, the computational nature of representation and inference in natural language makes it the ideal model for all tasks in an intelligent computer system. Natural language processing combines the qualitative characteristics of human knowledge processing with a computer's quantitative advantages, allowing for in-depth, systematic processing of vast amounts of information.

Book Synopsis Natural Language Processing and Knowledge Representation by : Łucja M. Iwańska

Download or read book Natural Language Processing and Knowledge Representation written by Łucja M. Iwańska and published by AAAI Press. This book was released on 2000-06-19 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Traditionally, knowledge representation and reasoning systems have incorporated natural language as interfaces to expert systems or knowledge bases that performed tasks separate from natural language processing. As this book shows, however, the computational nature of representation and inference in natural language makes it the ideal model for all tasks in an intelligent computer system. Natural language processing combines the qualitative characteristics of human knowledge processing with a computer's quantitative advantages, allowing for in-depth, systematic processing of vast amounts of information.

Representation and Processing of Natural Language

Author: Leonard Bolc

Publisher: Walter de Gruyter GmbH & Co KG

Published: 1980-12-31

Total Pages: 376

ISBN-13: 3112729196

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No detailed description available for "Representation and Processing of Natural Language".

Book Synopsis Representation and Processing of Natural Language by : Leonard Bolc

Download or read book Representation and Processing of Natural Language written by Leonard Bolc and published by Walter de Gruyter GmbH & Co KG. This book was released on 1980-12-31 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: No detailed description available for "Representation and Processing of Natural Language".

Introduction to Natural Language Processing

Author: Jacob Eisenstein

Publisher: MIT Press

Published: 2019-10-01

Total Pages: 535

ISBN-13: 0262042843

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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.

Book Synopsis Introduction to Natural Language Processing by : Jacob Eisenstein

Download or read book Introduction to Natural Language Processing written by Jacob Eisenstein and published by MIT Press. This book was released on 2019-10-01 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Knowledge-Based Intelligent Information and Engineering Systems

Author: Mircea Gh. Negoita

Publisher: Springer Science & Business Media

Published: 2004-09-20

Total Pages: 962

ISBN-13: 3540232052

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The three-volume set LNAI 3213, LNAI 3214, and LNAI 3215 constitutes the refereed proceedings of the 8th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2004, held in Wellington, New Zealand in September 2004. The over 450 papers presented were carefully reviewed and selected from numerous submissions. The papers present a wealth of original research results from the field of intelligent information processing in the broadest sense; among the areas covered are artificial intelligence, computational intelligence, cognitive technologies, soft computing, data mining, knowledge processing, various new paradigms in biologically inspired computing, and applications in various domains like bioinformatics, finance, signal processing etc.

Book Synopsis Knowledge-Based Intelligent Information and Engineering Systems by : Mircea Gh. Negoita

Download or read book Knowledge-Based Intelligent Information and Engineering Systems written by Mircea Gh. Negoita and published by Springer Science & Business Media. This book was released on 2004-09-20 with total page 962 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNAI 3213, LNAI 3214, and LNAI 3215 constitutes the refereed proceedings of the 8th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2004, held in Wellington, New Zealand in September 2004. The over 450 papers presented were carefully reviewed and selected from numerous submissions. The papers present a wealth of original research results from the field of intelligent information processing in the broadest sense; among the areas covered are artificial intelligence, computational intelligence, cognitive technologies, soft computing, data mining, knowledge processing, various new paradigms in biologically inspired computing, and applications in various domains like bioinformatics, finance, signal processing etc.

Speech & Language Processing

Author: Dan Jurafsky

Publisher: Pearson Education India

Published: 2000-09

Total Pages: 912

ISBN-13: 9788131716724

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Book Synopsis Speech & Language Processing by : Dan Jurafsky

Download or read book Speech & Language Processing written by Dan Jurafsky and published by Pearson Education India. This book was released on 2000-09 with total page 912 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Computational Semantics with Functional Programming

Author: Jan van Eijck

Publisher: Cambridge University Press

Published: 2010-09-23

Total Pages: 422

ISBN-13: 1139490907

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Computational semantics is the art and science of computing meaning in natural language. The meaning of a sentence is derived from the meanings of the individual words in it, and this process can be made so precise that it can be implemented on a computer. Designed for students of linguistics, computer science, logic and philosophy, this comprehensive text shows how to compute meaning using the functional programming language Haskell. It deals with both denotational meaning (where meaning comes from knowing the conditions of truth in situations), and operational meaning (where meaning is an instruction for performing cognitive action). Including a discussion of recent developments in logic, it will be invaluable to linguistics students wanting to apply logic to their studies, logic students wishing to learn how their subject can be applied to linguistics, and functional programmers interested in natural language processing as a new application area.

Book Synopsis Computational Semantics with Functional Programming by : Jan van Eijck

Download or read book Computational Semantics with Functional Programming written by Jan van Eijck and published by Cambridge University Press. This book was released on 2010-09-23 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational semantics is the art and science of computing meaning in natural language. The meaning of a sentence is derived from the meanings of the individual words in it, and this process can be made so precise that it can be implemented on a computer. Designed for students of linguistics, computer science, logic and philosophy, this comprehensive text shows how to compute meaning using the functional programming language Haskell. It deals with both denotational meaning (where meaning comes from knowing the conditions of truth in situations), and operational meaning (where meaning is an instruction for performing cognitive action). Including a discussion of recent developments in logic, it will be invaluable to linguistics students wanting to apply logic to their studies, logic students wishing to learn how their subject can be applied to linguistics, and functional programmers interested in natural language processing as a new application area.