Sabine Bergler – författare
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3 produkter
3 produkter
Häftad, Engelska, 1992
559 kr
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Recent work on formal methods in computational lexicalsemantics has had theeffect of bringing many linguisticformalisms much closer to the knowledge representationlanguages used in artificial intelligence. Formalisms arenow emerging which may be more expressive and formallybetter understood than many knowledge representationlanguages. The interests of computational linguists nowextend to include such domains as commonsense knowledge,inheritance, default reasoning, collocational relations, andeven domain knowledge. With such an extension of the normalpurview of "linguistic" knowledge, one may question whetherthere is any logical justification for distinguishingbetween lexical semantics and commonsense reasoning.This volume explores the question from severalmethodologicaland theoretical perspectives. What emerges isa clear consensus that the notion of the lexicon and lexicalknowledge assumed in earlier linguistic research is grosslyinadequate and fails to address the deeper semantic issuesrequired for natural language analysis.
Häftad, Engelska, 2008
559 kr
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This book constitutes the refereed proceedings of the 21st Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2008, held in Windsor, Canada, in May 2008. The 30 revised full papers presented together with 5 revised short papers were carefully reviewed and selected from 75 submissions. The papers present original high-quality research in all areas of Artificial Intelligence and apply historical AI techniques to modern problem domains as well as recent techniques to historical problem settings.
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This book constitutes the refereed proceedings of the 21st Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2008, held in Windsor, Canada, in May 2008. The 30 revised full papers presented together with 5 revised short papers were carefully reviewed and selected from 75 submissions. The papers present original high-quality research in all areas of Artificial Intelligence and apply historical AI techniques to modern problem domains as well as recent techniques to historical problem settings.