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  • 1
    Online Resource
    Online Resource
    Cambridge : Cambridge University Press
    UID:
    gbv_883358972
    Format: Online-Ressource (1 online resource (200 p.)) , digital, PDF file(s).
    Edition: Online-Ausg.
    ISBN: 9780511486579
    Series Statement: Studies in Natural Language Processing
    Content: Memory-based language processing - a machine learning and problem solving method for language technology - is based on the idea that the direct reuse of examples using analogical reasoning is more suited for solving language processing problems than the application of rules extracted from those examples. This book discusses the theory and practice of memory-based language processing, showing its comparative strengths over alternative methods of language modelling. Language is complex, with few generalizations, many sub-regularities and exceptions, and the advantage of memory-based language processing is that it does not abstract away from this valuable low-frequency information. By applying the model to a range of benchmark problems, the authors show that for linguistic areas ranging from phonology to semantics, it produces excellent results. They also describe TiMBL, a software package for memory-based language processing. The first comprehensive overview of the approach, this book will be invaluable for computational linguists, psycholinguists and language engineers
    Note: Title from publisher's bibliographic system (viewed on 05 Oct 2015) , 1. Memory-based learning in natural language processing -- 2. Inspirations from linguistics and artificial intelligence -- 3. Memory and similarity -- 4. Application to morpho-phonology -- 5. Application to shallow parsing -- 6. Abstraction and generalization -- 7. Extensions.
    Additional Edition: ISBN 9780521808903
    Additional Edition: ISBN 9780521114455
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-052-180-890-3
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9780521808903
    Language: English
    URL: Volltext  (lizenzpflichtig)
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Online Resource
    Online Resource
    Cambridge :Cambridge University Press,
    UID:
    almafu_9959243209102883
    Format: 1 online resource (vii, 189 pages) : , digital, PDF file(s).
    ISBN: 1-107-14404-3 , 1-280-45824-0 , 0-511-19119-7 , 0-511-16142-5 , 0-511-16014-3 , 0-511-30044-1 , 0-511-48657-X , 0-511-16071-2
    Series Statement: Studies in natural language processing
    Content: Memory-based language processing - a machine learning and problem solving method for language technology - is based on the idea that the direct reuse of examples using analogical reasoning is more suited for solving language processing problems than the application of rules extracted from those examples. This book discusses the theory and practice of memory-based language processing, showing its comparative strengths over alternative methods of language modelling. Language is complex, with few generalizations, many sub-regularities and exceptions, and the advantage of memory-based language processing is that it does not abstract away from this valuable low-frequency information. By applying the model to a range of benchmark problems, the authors show that for linguistic areas ranging from phonology to semantics, it produces excellent results. They also describe TiMBL, a software package for memory-based language processing. The first comprehensive overview of the approach, this book will be invaluable for computational linguists, psycholinguists and language engineers.
    Note: Title from publisher's bibliographic system (viewed on 05 Oct 2015). , Memory-based learning in natural language processing -- , Inspirations from linguistics and artificial intelligence -- , Memory and similarity -- , Application to morpho-phonology -- , Application to shallow parsing -- , Abstraction and generalization -- , Extensions. , English
    Additional Edition: ISBN 0-521-11445-4
    Additional Edition: ISBN 0-521-80890-1
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
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