Ambiguity Resolution in Language Learning: Computational and Cognitive Models

Author:   Hinrich Schütze (Xerox Palo Alto Research Center, Stanford University, California)
Publisher:   Centre for the Study of Language & Information
Edition:   74th ed.
Volume:   71
ISBN:  

9781575860756


Pages:   230
Publication Date:   13 May 1997
Format:   Hardback
Availability:   In stock   Availability explained
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Ambiguity Resolution in Language Learning: Computational and Cognitive Models


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Overview

This volume is concerned with how ambiguity and ambiguity resolution are learned, that is, with the acquisition of the different representations of ambiguous linguistic forms and the knowledge necessary for selecting among them in context. Schütze concentrates on how the acquisition of ambiguity is possible in principle and demonstrates that particular types of algorithms and learning architectures (such as unsupervised clustering and neural networks) can succeed at the task. Three types of lexical ambiguity are treated: ambiguity in syntactic categorisation, semantic categorisation, and verbal subcategorisation. The volume presents three different models of ambiguity acquisition: Tag Space, Word Space, and Subcat Learner, and addresses the importance of ambiguity in linguistic representation and its relevance for linguistic innateness.

Full Product Details

Author:   Hinrich Schütze (Xerox Palo Alto Research Center, Stanford University, California)
Publisher:   Centre for the Study of Language & Information
Imprint:   Centre for the Study of Language & Information
Edition:   74th ed.
Volume:   71
Dimensions:   Width: 15.20cm , Height: 2.30cm , Length: 22.80cm
Weight:   0.530kg
ISBN:  

9781575860756


ISBN 10:   1575860759
Pages:   230
Publication Date:   13 May 1997
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In stock   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

Table of Contents

Acknowledgements; 1. Introduction; 2. Syntactic categorisation; 3. Semantic categorisation; 4. Subcategorization; 5. A look back; 6. Appendix A: mathematical methods; References.

Reviews

The book is an enlightening investigation into the relationship between ambiguity resolution and language learning. It is unique in its focus on the disambiguation problem in leanrning, rather than in processing, in contrast to the main concern of much research in the NLP literature. I. Dan Melamed, Computational Linguistics


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