Handbook of Natural Language Processing, Second Edition
Purchasing Options
Features
- Explores the practical aspects of building natural language processing systems
- Covers many well-known and emerging applications, including machine translation, biomedical text mining, and sentiment analysis
- Provides examples of how to apply the techniques to languages other than English
- Offers web links, supplementary material, and updates to chapters on a companion wiki: http://handbookofnlp.cse.unsw.edu.au
Summary
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 Along with removing outdated material, this edition updates every chapter and expands the content to include emerging areas, such as sentiment analysis.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.
Table of Contents
CLASSICAL APPROACHES
Classical Approaches to Natural Language Processing, Robert Dale
Text Preprocessing, David D. Palmer
Lexical Analysis, Andrew Hippisley
Syntactic Parsing, Peter Ljunglöf and Mats Wirén
Semantic Analysis, Cliff Goddard and Andrea C. Schalley
Natural Language Generation, David D. McDonald
EMPIRICAL AND STATISTICAL APPROACHES
Corpus Creation, Richard Xiao
Treebank Annotation, Eva Hajičová, Anne Abeillé, Jan Hajič, Jiři Mirovský, and Zdeňka Urešová
Fundamental Statistical Techniques, Tong Zhang
Part-of-Speech Tagging, Tunga Güngör
Statistical Parsing, Joakim Nivre
Multiword Expressions, Timothy Baldwin and Su Nam Kim
Normalized Web Distance and Word Similarity, Paul M.B. Vitányi and Rudi L. Cilibrasi
Word-Sense Disambiguation, David Yarowsky
An Overview of Modern Speech Recognition, Xuedong Huang and Li Deng
Alignment, Dekai Wu
Statistical Machine Translation, Abraham Ittycheriah
APPLICATIONS
Chinese Machine Translation, Pascale Fung
Information Retrieval, Jacques Savoy and Eric Gaussier
Question Answering, Diego Mollá-Aliod and José-Luis Vicedo
Information Extraction, Jerry R. Hobbs and Ellen Riloff
Report Generation, Leo Wanner
Emerging Applications of Natural Language Generation in Information Visualization, Education, and Healthcare, Barbara Di Eugenio and Nancy L. Green
Ontology Construction, Philipp Cimiano, Johanna Völker, and Paul Buitelaar
BioNLP: Biomedical Text Mining, K. Bretonnel Cohen
Sentiment Analysis and Subjectivity, Bing Liu
Index
Author Bio(s)
Editorial Reviews
… 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
