Handbook of natural language processing

✍ Scribed by Nitin Indurkhya; Frederick J Damerau (eds.)

• Publisher: Chapman & Hall/CRC
• Year: 2010
• Tongue: English
• Leaves: 692
• Series: Chapman & Hall/CRC machine learning & pattern recognition series
• Edition: 2ed.
• Category: Library

✦ Synopsis

The purpose of the research in this volume is to design a machine-tractable dictionary from the Longman Dictionary of Contemporary English (LDOCE). A machine-tractable dictionary is intended to be a basic facility for a whole spectrum of natural language processing tasks. The research adopts a compositional-reduction approach to obtain a set of empirically derived definitional primitives and use them to construct formalized sense entries in a nested predicate form where the predicates are a set of definitional primitives called "seed senses". Over 40 years of continuous effort at natural language processing have led the research community in this area to the realization that very large machine tractable dictionaries are essential to success in any further computational attempts at natural language. The emergence of machine-readable data, such as dictionaries, encyclopedias, and documents of a general, unrestricted nature as by-products of modern typesetting technology, facilitates the derivation of very large lexicons and knowledge bases at low costs. An open research question in computation lexicography in particular and natural language processing in general involves the machine tractability of these lexicons. A lexicon is machine tractable only when it assists copmuter understanding of natural language text as well as the acquisition of new lexical and world knowledge by the computer "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 Along with removing outdated material, this edition updates every chapter and expands the content to include emerging areas, such as sentiment analysis."-- BOOK JACKET. Classical approaches to natural language processing / Robert Dale -- Text preprocessing / Davis D. Palmer -- Lexical analysis / Andrew Hippisley -- Syntactic parsing / Peter Ljunglöf and Mats Wirén -- Semantic analysis / Cliff Goddard and Andrea C. Schalley -- Natural language generation / Davis D. McDonald -- Corpus creation / Richard Xiao -- Treebank annotation / Eva Hajičová ... [et al.] -- 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 / Davis Yarowsky -- An overview of modern speech recognition / Xuedong Huang and Li Deng -- Alignment / Dekai Wu -- Statistical machine translation / Abraham Ittycheriah -- 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 health care / Barbara Di Eugenio and Nancy L. Green -- Ontology construction / Philipp Cimiano, Johanna Völker, and Paul Buitelaar -- BioNPL: biomedical text mining / K. Bretonnel Cohen -- Sentiment analysis and subjectivity / Bing Liu