Natural Language Processing Using Very Large Corpora [electronic resource] /

ABOUT THIS BOOK This book is intended for researchers who want to keep abreast of cur­ rent developments in corpus-based natural language processing. It is not meant as an introduction to this field; for readers who need one, several entry-level texts are available, including those of (Church and Mercer, 1993; Charniak, 1993; Jelinek, 1997). This book captures the essence of a series of highly successful work­ shops held in the last few years. The response in 1993 to the initial Workshop on Very Large Corpora (Columbus, Ohio) was so enthusias­ tic that we were encouraged to make it an annual event. The following year, we staged the Second Workshop on Very Large Corpora in Ky­ oto. As a way of managing these annual workshops, we then decided to register a special interest group called SIGDAT with the Association for Computational Linguistics. The demand for international forums on corpus-based NLP has been expanding so rapidly that in 1995 SIGDAT was led to organize not only the Third Workshop on Very Large Corpora (Cambridge, Mass. ) but also a complementary workshop entitled From Texts to Tags (Dublin). Obviously, the success of these workshops was in some measure a re­ flection of the growing popularity of corpus-based methods in the NLP community. But first and foremost, it was due to the fact that the work­ shops attracted so many high-quality papers.

Bibliographic Details

Main Authors:	Armstrong, Susan. editor., Church, Kenneth. editor., Isabelle, Pierre. editor., Manzi, Sandra. editor., Tzoukermann, Evelyne. editor., Yarowsky, David. editor., SpringerLink (Online service)
Format:	Texto biblioteca
Language:	eng
Published:	Dordrecht : Springer Netherlands : Imprint: Springer, 1999
Subjects:	Linguistics., Artificial intelligence., Computational linguistics., Electrical engineering., Computational Linguistics., Artificial Intelligence (incl. Robotics)., Electrical Engineering.,
Online Access:	http://dx.doi.org/10.1007/978-94-017-2390-9
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