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Word Sense Disambiguation: Algorithms and Applications: 33 (Text, Speech and Language Technology) - Hardcover

 
9781402048081: Word Sense Disambiguation: Algorithms and Applications: 33 (Text, Speech and Language Technology)

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This is the first comprehensive book to cover all aspects of word sense disambiguation. It covers major algorithms, techniques, performance measures, results, philosophical issues and applications. The text synthesizes past and current research across the field, and helps developers grasp which techniques will best apply to their particular application, how to build and evaluate systems, and what performance to expect. An accompanying Website extends the effectiveness of the text.

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This is the first book to cover the entire topic of word sense disambiguation (WSD) including: all the major algorithms, techniques, performance measures, results, philosophical issues, and applications. Leading researchers in the field have contributed chapters that synthesize and provide an overview of past and state-of-the-art research across the field. The editors have carefully organized the chapters into sub-topics. Researchers and lecturers will learn about the full range of what has been done and where the field is headed. Developers will learn which technique(s) will apply to their particular application, how to build and evaluate systems, and what performance to expect. An accompanying Website (www.wsdbook.org) provides links to resources for WSD and a searchable index of the book.

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9781402068706: Word Sense Disambiguation: Algorithms and Applications: 33 (Text, Speech and Language Technology)

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ISBN 10:  1402068700 ISBN 13:  9781402068706
Verlag: Springer, 2007
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AGIRRE, Eneko, Philip Edmonds (Edits).
Verlag: Springer,, Dordrecht,, 2006
ISBN 10: 1402048084 ISBN 13: 9781402048081
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Hardback. Zustand: Fine. First Edition. Hardback. 8vo. Original publisher's laminated boards. Issued without dust jacket. ISBN: 1402048084 Pages: 366 May show some very slight shelf wear but content fine and unread. Ê. Artikel-Nr. C61193

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Buch. Zustand: Neu. Neuware -Graeme Hirst University of Toronto Of the many kinds of ambiguity in language, the two that have received the most attention in computational linguistics are those of word senses and those of syntactic structure, and the reasons for this are clear: these ambiguities are overt, their resolution is seemingly essential for any prac- cal application, and they seem to require a wide variety of methods and knowledge-sources with no pattern apparent in what any particular - stance requires. Right at the birth of artificial intelligence, in his 1950 paper ¿Computing machinery and intelligence¿, Alan Turing saw the ability to understand language as an essential test of intelligence, and an essential test of l- guage understanding was an ability to disambiguate; his example involved deciding between the generic and specific readings of the phrase a winter¿s day. The first generations of AI researchers found it easy to construct - amples of ambiguities whose resolution seemed to require vast knowledge and deep understanding of the world and complex inference on this kno- edge; for example, Pharmacists dispense with accuracy. The disambig- tion problem was, in a way, nothing less than the artificial intelligence problem itself. No use was seen for a disambiguation method that was less than 100% perfect; either it worked or it didn¿t. Lexical resources, such as they were, were considered secondary to non-linguistic common-sense knowledge of the world.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 392 pp. Englisch. Artikel-Nr. 9781402048081

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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Graeme Hirst University of Toronto Of the many kinds of ambiguity in language, the two that have received the most attention in computational linguistics are those of word senses and those of syntactic structure, and the reasons for this are clear: these ambiguities are overt, their resolution is seemingly essential for any prac- cal application, and they seem to require a wide variety of methods and knowledge-sources with no pattern apparent in what any particular - stance requires. Right at the birth of artificial intelligence, in his 1950 paper 'Computing machinery and intelligence', Alan Turing saw the ability to understand language as an essential test of intelligence, and an essential test of l- guage understanding was an ability to disambiguate; his example involved deciding between the generic and specific readings of the phrase a winter's day. The first generations of AI researchers found it easy to construct - amples of ambiguities whose resolution seemed to require vast knowledge and deep understanding of the world and complex inference on this kno- edge; for example, Pharmacists dispense with accuracy. The disambig- tion problem was, in a way, nothing less than the artificial intelligence problem itself. No use was seen for a disambiguation method that was less than 100% perfect; either it worked or it didn't. Lexical resources, such as they were, were considered secondary to non-linguistic common-sense knowledge of the world. Artikel-Nr. 9781402048081

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Verlag: Springer, 2006
ISBN 10: 1402048084 ISBN 13: 9781402048081
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