Machine Learning of Natural Language

David M. W. Powers

ISBN 10: 3540195572 / ISBN 13: 9783540195573

Published by Springer, Springer, 1989

About this Item

Druck auf Anfrage Neuware - Printed after ordering - We met because we both share the same views of language. Language is a living organism, produced by neural mechanisms relating in large numbers as a society. Language exists between minds, as a way of communicating between them, not as an autonomous process. The logical 'rules' seem to us an epiphe nomena of the neural mechanism, rather than an essential component in language. This view of language has been advocated by an increasing number of workers, as the view that language is simply a collection of logical rules has had less and less success. People like Yorick Wilks have been able to show in paper after paper that almost any rule which can be devised can be shown to have exceptions. The meaning does not lie in the rules. David Powers is a teacher of computer science. Christopher Turk, like many workers who have come into the field of AI (Artificial Intelligence) was originally trained in literature. He moved into linguistics, and then into computational linguistics. In 1983 he took a sabbatical in Roger Shank's AI project in the Computer Science Department at Yale University. Like an earlier visitor to the project, John Searle from California, Christopher Turk was increasingly uneasy at the view of language which was used at Yale.; We are still a long way from designing computers that can understand human languages. The authors view natural language as fundamental to human cognitive processes and perhaps the key to making machines that can understand us. In this electronic age, language is increasingly the province of workers in the fields of cognitive psychology and artificial intelligence who record, transmit, simulate and analyse its form and representation. The authors explore current thinking in the search for machine understanding of human languages, focusing on how computing machinery can acquire the cognitive structures which occur in natural language. The book begins with a summary of basic views of methodology, bringing together linguistic, scientific, neurological and related cognitive approaches. It concludes with a description of experimental learning mechanisms, some of which are simplifications of the way a natural language acquisition system might be built, and some example programs in PROLOG. Die Autoren erforschen aktuelle Denkrichtungen, die das Ziel haben, daß Maschinen natürliche Sprachen verstehen. Zunächst wird eine Zusammenfassung der grundlegenden Methodik gegeben; am Schluß werden experimentelle Lernmechanismen und Beispielprogramme in PROLOG beschrieben.

Seller Inventory # 9783540195573

Bibliographic Details

• Title: Machine Learning of Natural Language
• Publisher: Springer, Springer
• Publication Date: 1989
• Language: English
• ISBN 10: 3540195572
• ISBN 13: 9783540195573
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 242W x 170H x 21D millimeters 242 millimeters width by 170 millimeters height by 21 millimeters depth
• Weight: 636 grams

About this title

Synopsis

We met because we both share the same views of language. Language is a living organism, produced by neural mechanisms relating in large numbers as a society. Language exists between minds, as a way of communicating between them, not as an autonomous process. The logical 'rules' seem to us an epiphe­ nomena ·of the neural mechanism, rather than an essential component in language. This view of language has been advocated by an increasing number of workers, as the view that language is simply a collection of logical rules has had less and less success. People like Yorick Wilks have been able to show in paper after paper that almost any rule which can be devised can be shown to have exceptions. The meaning does not lie in the rules. David Powers is a teacher of computer science. Christopher Turk, like many workers who have come into the field of AI (Artificial Intelligence) was originally trained in literature. He moved into linguistics, and then into computational linguistics. In 1983 he took a sabbatical in Roger Shank's AI project in the Computer Science Department at Yale University. Like an earlier visitor to the project, John Searle from California, Christopher Turk was increasingly uneasy at the view of language which was used at Yale.