Isbn: 9781402048081 - word sense disambiguation: algorithms and applications: 33 (13 risultati)

Soft cover. Condizione: New. Condizione sovraccoperta: New. 1st Edition. **INTERNATIONAL EDITION** Read carefully before purchase: This book is the international edition in mint condition with the different ISBN and book cover design, the major content is printed in full English as same as the original North American edition. The book printed in black and white, generally send in twenty-four hours after the order confirmed. All shipments go through via USPS/UPS/DHL with tracking numbers. Great professional textbook selling experience and expedite shipping service.…

Hardback. Condizione: 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.

Condizione: New.

Condizione: New.

Condizione: New. In English.

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Buch. Condizione: 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.…

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Hardcover. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 380 pp. Englisch.…

Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The first book to cover all aspects of word sense disambiguation Contains contributions by leading researchers in the fieldThe first book to cover all aspects of word sense disambiguationContains contributions by leading research.…

Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. 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 KG, Sachsenplatz 4-6, 1201 Wien 392 pp. Englisch. …