Using Large Corpora

Using Large Corpora

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Using Large Corpora identifies new data-oriented methods for organizing and analyzing large corpora and describes the potential results that the use of large corpora offers.

Today, large corpora consisting of hundreds of millions or even billions of words, along with new empirical and statistical methods for organizing and analyzing these data, promise new insights into the use of language. Already, the data extracted from these large corpora reveal that language use is more flexible and complex than most rule-based systems have tried to account for, providing a basis for progress in the performance of Natural Language Processing systems. Using Large Corpora identifies these new data-oriented methods and describes the potential results that the use of large corpora offers. The research described shows that the new methods may offer solutions to key issues of acquisition (automatically identifying and coding information), coverage (accounting for all of the phenomena in a given domain), robustness (accommodating "real data" that may be corrupt or not accounted for in the model), and extensibility (applying the model and data to a new domain, text, or problem). There are chapters on lexical issues, issues in syntax, and translation topics, as well discussions of the "statistics-based" vs. "rule-based" debate. ACL-MIT Series in Natural Language Processing.
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Product details

  • Paperback | 359 pages
  • 175 x 249 x 23mm | 748g
  • Bradford Books
  • Massachusetts, United States
  • English
  • 0262510820
  • 9780262510820
  • 1,074,365

Table of contents

Introduction to the special issue on computational linguistics using large corpora, Kenneth W. Church and Robert L. Mercer; generalized probabilistic LR parsing of natural language (corpora) with unification-based grammars, Ted Briscoe and John Carroll; accurate methods for the statistics of surprise and coincidence, Ted Dunning; a program for aligning sentences in bilingual corpora, William A. Gale and Kenneth W. Church; structural ambiguity and lexical relations, Donald Hindle and Mats Rooth; text-translation alignment, Martin Kay and Martin Roescheisen; retrieving collocations from text - Xtract, Frank Smadja; using register-diversified corpora for general language studies, Douglas Biber; from grammar to lexicon - unsupervised learning of lexical syntax, Michael R. Brent; the mathematics of statistical machine translation - parameter estimation, Peter F. Brown et al; building a large annotated corpus of English - the Penn treebank, Mitchell P. Marcus et al; lexical semantic techniques for corpus analysis, James Pustejovsky et al; coping with ambiguity and unknown words through probabilistic models, Ralph Weischedel et al.
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About Maurice V. Wilkes

Maurice Wilkes retired from his post at Cambridge University in 1980, when he became a Senior Consulting Engineer at Digital Equipment Corporation in Massachusetts and Adjunct Professor at MIT.
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