2nd Edition

Handbook of Natural Language Processing

Edited By Nitin Indurkhya, Fred J. Damerau Copyright 2010
    702 Pages 115 B/W Illustrations
    by Chapman & Hall

    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 Along with removing outdated material, this edition updates every chapter and expands the content to include emerging areas, such as sentiment analysis.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.

    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

    Biography

    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.

    … 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

    … the handbook covers the wide area of NLP and its applications. This will essentially help researchers and graduate students to access starting-point material for a particular area of interest. The handbook also covers the associated algorithms with examples which will help to develop prototype systems … a high quality compilation of up-to-date theories and applications of NLP.
    — Sandipan Dandapat

    … 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