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Automatic Ambiguity Resolution in Natural Language Processing: An Empirical Approach: 1171 (Lecture Notes in Artificial Intelligence) - Tapa blanda
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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.
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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.
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Automatic Ambiguity Resolution in Natural Language Processing: An Empirical Approach (Lecture Notes in Computer Science, 1171)
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Automatic Ambiguity Resolution in Natural Language Processing : An Empirical Approach
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Springer Berlin Heidelberg, 1996
ISBN 10: 3540620044
ISBN 13: 9783540620044
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Automatic Ambiguity Resolution in Natural Language Processing: An Empirical Approach (Lecture Notes in Computer Science, 1171)
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Automatic Ambiguity Resolution in Natural Language Processing : An Empirical Approach
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Springer Berlin Heidelberg, 1996
ISBN 10: 3540620044
ISBN 13: 9783540620044
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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Nº de ref. del artículo: 9783540620044
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Automatic Ambiguity Resolution in Natural Language Processing
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Springer Berlin Heidelberg, 1996
ISBN 10: 3540620044
ISBN 13: 9783540620044
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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.T. Nº de ref. del artículo: 4895838
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Automatic Ambiguity Resolution in Natural Language Processing : An Empirical Approach
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Automatic Ambiguity Resolution in Natural Language Processing
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Springer Berlin Heidelberg Nov 1996, 1996
ISBN 10: 3540620044
ISBN 13: 9783540620044
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 184 pp. Englisch. Nº de ref. del artículo: 9783540620044
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Automatic Ambiguity Resolution in Natural Language Processing
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Springer Berlin Heidelberg Nov 1996, 1996
ISBN 10: 3540620044
ISBN 13: 9783540620044
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 184 pp. Englisch. Nº de ref. del artículo: 9783540620044
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Automatic Ambiguity Resolution in Natural Language Processing: An Empirical Approach (Lecture Notes in Computer Science, 1171)
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