Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing

Stefan Wermter

ISBN 10: 3540609253 / ISBN 13: 9783540609254

Verlag: Springer Berlin Heidelberg Mrz 1996, 1996

Beschreibung

This item is printed on demand - it takes 3-4 days longer - Neuware -This book is based on the workshop on New Approaches to Learning for Natural Language Processing, held in conjunction with the International Joint Conference on Artificial Intelligence, IJCAI'95, in Montreal, Canada in August 1995.Most of the 32 papers included in the book are revised selected workshop presentations; some papers were individually solicited from members of the workshop program committee to give the book an overall completeness. Also included, and written with the novice reader in mind, is a comprehensive introductory survey by the volume editors. The volume presents the state of the art in the most promising current approaches to learning for NLP and is thus compulsory reading for researchers in the field or for anyone applying the new techniques to challenging real-world NLP problems. 484 pp. Englisch.

Bestandsnummer des Verkäufers 9783540609254

Bibliografische Details

• Titel: Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing
• Verlag: Springer Berlin Heidelberg Mrz 1996
• Veröffentlichungsdatum: 1996
• Sprache: Englisch
• ISBN-10: 3540609253
• ISBN-13: 9783540609254
• Bindung: Taschenbuch
• Zustand: Neu

Über diesen Titel

Inhaltsangabe

This book is based on the workshop on New Approaches to Learning for Natural Language Processing, held in conjunction with the International Joint Conference on Artificial Intelligence, IJCAI'95, in Montreal, Canada in August 1995.
Most of the 32 papers included in the book are revised selected workshop presentations; some papers were individually solicited from members of the workshop program committee to give the book an overall completeness. Also included, and written with the novice reader in mind, is a comprehensive introductory survey by the volume editors. The volume presents the state of the art in the most promising current approaches to learning for NLP and is thus compulsory reading for researchers in the field or for anyone applying the new techniques to challenging real-world NLP problems.