Handbook of Natural Language Processing
The Handbook of Natural Language Processing, Second Edition presents practical tools and techniques for implementing natural language processing in computer systems. Along with removing outdated material, this edition updates every chapter and expands the content to include emerging areas, such as sentiment analysis.

New to the Second Edition

  • Greater prominence of statistical approaches
  • New applications section
  • Broader multilingual scope to include Asian and European languages, along with English
  • An actively maintained wiki (http://handbookofnlp.cse.unsw.edu.au) that provides online resources, supplementary information, and up-to-date developments

Divided into three sections, the book first surveys classical techniques, including both symbolic and empirical approaches. The second section focuses on statistical approaches in natural language processing. In the final section of the book, each chapter describes a particular class of application, from Chinese machine translation to information visualization to ontology construction to biomedical text mining. Fully updated with the latest developments in the field, this comprehensive, modern handbook emphasizes how to implement practical language processing tools in computational systems.

1108006229
Handbook of Natural Language Processing
The Handbook of Natural Language Processing, Second Edition presents practical tools and techniques for implementing natural language processing in computer systems. Along with removing outdated material, this edition updates every chapter and expands the content to include emerging areas, such as sentiment analysis.

New to the Second Edition

  • Greater prominence of statistical approaches
  • New applications section
  • Broader multilingual scope to include Asian and European languages, along with English
  • An actively maintained wiki (http://handbookofnlp.cse.unsw.edu.au) that provides online resources, supplementary information, and up-to-date developments

Divided into three sections, the book first surveys classical techniques, including both symbolic and empirical approaches. The second section focuses on statistical approaches in natural language processing. In the final section of the book, each chapter describes a particular class of application, from Chinese machine translation to information visualization to ontology construction to biomedical text mining. Fully updated with the latest developments in the field, this comprehensive, modern handbook emphasizes how to implement practical language processing tools in computational systems.

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Handbook of Natural Language Processing

Handbook of Natural Language Processing

Handbook of Natural Language Processing

Handbook of Natural Language Processing

Hardcover(2nd ed.)

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Overview

The Handbook of Natural Language Processing, Second Edition presents practical tools and techniques for implementing natural language processing in computer systems. Along with removing outdated material, this edition updates every chapter and expands the content to include emerging areas, such as sentiment analysis.

New to the Second Edition

  • Greater prominence of statistical approaches
  • New applications section
  • Broader multilingual scope to include Asian and European languages, along with English
  • An actively maintained wiki (http://handbookofnlp.cse.unsw.edu.au) that provides online resources, supplementary information, and up-to-date developments

Divided into three sections, the book first surveys classical techniques, including both symbolic and empirical approaches. The second section focuses on statistical approaches in natural language processing. In the final section of the book, each chapter describes a particular class of application, from Chinese machine translation to information visualization to ontology construction to biomedical text mining. Fully updated with the latest developments in the field, this comprehensive, modern handbook emphasizes how to implement practical language processing tools in computational systems.


Product Details

ISBN-13: 9781420085921
Publisher: Taylor & Francis
Publication date: 02/22/2010
Series: Chapman & Hall/CRC Machine Learning & Pattern Recognition
Edition description: 2nd ed.
Pages: 702
Product dimensions: 7.00(w) x 10.40(h) x 1.50(d)

About the Author

Nitin Indurkhya is an associate professor in the School of Computer Science and Engineering at the University of New South Wales in Sydney, Australia. He is also the founder and president of Data-Miner Pty Ltd, which offers education, training, and consulting services in data/text analytics and human language technologies.

Before his death, Fred J. Damerau was a researcher at IBM’s Thomas J. Watson Research Center in Yorktown Heights, New York, where he worked on machine learning approaches to natural language processing.

Table of Contents

Classical Approaches. Empirical and Statistical Approaches. Applications. Index.

What People are Saying About This

From the Publisher

… The need for a revised second edition of this book arose because of the growth of the field and the introduction of new methods. … The chapters have been exhaustively reviewed to maintain quality and homogeneity. The handbook has numerous diagrams and tables. The chapters are arranged so that they may be read independently. The style of presentation is good and the index is useful. Adequate references to current literature are provided. When compared to the previous edition, this edition focuses on statistical approaches, new and emerging applications, and multilingual scope, and has an actively maintained Wiki. Outdated chapters present in the first edition have been removed, and the remaining chapters have been rewritten and updated to reflect current trends and applications. When compared to other handbooks on NLP, this one is cheaper and certainly worth every penny. It provides a lot of useful information to those who are interested in NLP and its applications. … I highly recommend this handbook to practitioners of NLP as a very useful resource.
Computing Reviews, January 2011

… If you need a readable introduction to this important subject — this is it. … This is a good way to get into NLP. … this does provide a basic course on the subject suitable both for academic and practical development. Highly recommended.
—Mike James, iProgrammer, 2010

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