Sinopsis
Investigations into employing statistical approaches with linguistically motivated representations and its impact on Natural Language processing tasks.
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Acerca de los autores
Srinivas Bangalore is Principal Technical Staff Member at AT&T Labs-Research. He was awarded the AT&T Science and Technology Medal in 2009 for technical leadership and innovative contributions in Spoken Language Technology and Services.
Aravind K. Joshi is Henry Salvatori Professor of Computer and Cognitive Science at the University of Pennsylvania. He received the David Rumelhart Prize for fundamental theoretical contributions to the cognitive sciences in 2003.
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Supertagging: Using Complex Lexical Descriptions in Natural Language Processing (A Bradford Book)
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A Bradford Book, 2010
ISBN 10: 0262013878
ISBN 13: 9780262013871
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Librería: Midtown Scholar Bookstore, Harrisburg, PA, Estados Unidos de America
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Hardcover. Condición: Very Good. crisp clean w/light shelfwear/edgewear - may have remainder mark Standard-sized. Nº de ref. del artículo: 0262013878-01
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Supertagging: Using Complex Lexical Descriptions in Natural Language Processing
Librería: Powell's Bookstores Chicago, ABAA, Chicago, IL, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Condición: Used - Very Good. 2010. Hardcover. Cloth, dj. Slight shelf wear. Very Good. Nº de ref. del artículo: SIN0010846
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Supertagging: Using Complex Lexical Descriptions in Natural Language Processing.
Publicado por
Bradford Books, 2010
ISBN 10: 0262013878
ISBN 13: 9780262013871
Antiguo o usado
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Librería: Kloof Booksellers & Scientia Verlag, Amsterdam, Holanda
Calificación del vendedor: 4 de 5 estrellas
Condición: as new. Cambridge, MA : The MIT Press, 2010. Hardcover. Dustjacket. 512 pp.- The last decade has seen computational implementations of large hand-crafted natural language grammars in formal frameworks such as Tree-Adjoining Grammar (TAG), Combinatory Categorical Grammar (CCG), Head-driven Phrase Structure Grammar (HPSG), and Lexical Functional Grammar (LFG). Grammars in these frameworks typically associate linguistically motivated rich descriptions (Supertags) with words. With the availability of parse-annotated corpora, grammars in the TAG and CCG frameworks have also been automatically extracted while maintaining the linguistic relevance of the extracted Supertags. In these frameworks, Supertags are designed so that complex linguistic constraints are localized to operate within the domain of those descriptions. While this localization increases local ambiguity, the process of disambiguation (Supertagging) provides a unique way of combining linguistic and statistical information. This volume investigates the theme of employing statistical approaches with linguistically motivated representations and its impact on Natural Language Processing tasks. In particular, the contributors describe research in which words are associated with Supertags that are the primitives of different grammar formalisms including Lexicalized Tree-Adjoining Grammar (LTAG). ContributorsJens Bäcker, Srinivas Bangalore, Akshar Bharati, Pierre Boullier, Tomas By, John Chen, Stephen Clark, Berthold Crysmann, James R. Curran, Kilian Foth, Robert Frank, Karin Harbusch, Sa?a Hasan, Aravind Joshi,Vincenzo Lombardo, Takuya Matsuzaki, Alessandro Mazzei, Wolfgang Menzel, Yusuke Miyao, Richard Moot, Alexis Nasr, Günter Neumann, Martha Palmer, Owen Rambow, Rajeev Sangal, Anoop Sarkar, Giorgio Satta, Libin Shen, Patrick Sturt, Jun'ichi Tsujii, K. Vijay-Shanker, Wen Wang, Fei XiaEnglish text. Condition : a Condition : as new copy. ISBN 9780262013871. Keywords : , Nº de ref. del artículo: 242962
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Supertagging :Using Complex Lexical Descriptions in Natural Language Processing
Librería: Anybook.com, Lincoln, Reino Unido
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Condición: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. Dust jacket in good condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1100grams, ISBN:9780262013871. Nº de ref. del artículo: 9546584
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