Automatic Ambiguity Resolution in Natural Language Processing: An Empirical Approach / Edition 1

by Alexander Franz

Overview

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.

Product Details

ISBN-13:	9783540620044
Publisher:	Springer Berlin Heidelberg
Publication date:	12/05/1996
Series:	Lecture Notes in Computer Science , #1171
Edition description:	1996
Pages:	164
Product dimensions:	6.10(w) x 9.25(h) x 0.36(d)

Table of Contents

Previous work on syntactic ambiguity resolution.- Loglinear models for ambiguity resolution.- Modeling new words.- Part-of-speech ambiguity.- Prepositional phrase attachment disambiguation.- Conclusions.