Automatic Ambiguity Resolution in Natural Language Processing

An Empirical Approach

  • Editors
  • Alexander Franz

Part of the Lecture Notes in Computer Science book series (LNCS, volume 1171)

Table of contents

About this book


This is an exciting time for Artificial Intelligence, and for Natural Language Processing in particular. Over the last five years or so, a newly revived spirit has gained prominence that promises to revitalize the whole field: the spirit of empiricism.
This book introduces a new approach to the important NLP issue of automatic ambiguity resolution, based on statistical models of text. This approach is compared with previous work and proved to yield higher accuracy for natural language analysis. An effective implementation strategy is also described, which is directly useful for natural language analysis. The book is noteworthy for demonstrating a new empirical approach to NLP; it is essential reading for researchers in natural language processing or computational linguistics.


Ambiguity Resolution Corpusbasierte Natürlichsprachliche Verarbeitung Empirische Künstiche Intelligenz artificial intelligence computational linguistics corpus-based NLP intelligence linguistics modeling natural language natural language analysi

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 1996
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-62004-4
  • Online ISBN 978-3-540-49593-2
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book