
Automatic Ambiguity Resolution in Natural Language Processing
An Empirical Approach
Alexander Franz(Author)
Springer (Publisher)
Published on 13. November 1996
Book
Paperback/Softback
XX, 164 pages
978-3-540-62004-4 (ISBN)
Description
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.
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.
More details
Series
Edition
1996 ed.
Language
English
Place of publication
Berlin
Germany
Publishing group
Springer Berlin
Target group
Professional and scholarly
Research
Illustrations
XX, 164 p.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 11 mm
Weight
289 gr
ISBN-13
978-3-540-62004-4 (9783540620044)
DOI
10.1007/BFb0021059
Schweitzer Classification
Content
Previous work on syntactic ambiguity resolution.- Loglinear models for ambiguity resolution.- Modeling new words.- Part-of-speech ambiguity.- Prepositional phrase attachment disambiguation.- Conclusions.