Sabine Bergler - Böcker
Visar alla böcker från författaren Sabine Bergler. Handla med fri frakt och snabb leverans.
2 produkter
2 produkter
Lexical Semantics and Knowledge Representation
First SIGLEX Workshop, Berkeley, CA, USA, June 17, 1991. Proceedings
Häftad, Engelska, 1992
551 kr
Skickas inom 10-15 vardagar
Recent work on formal methods in computational lexical semantics has had the effect of bringing many linguistic formalisms much closer to the knowledge representation languages used in artificial intelligence. Formalisms are now emerging which may be more expressive and formally better understood than many knowledge representation languages. The interests of computational linguists now extend to include such domains as commonsense knowledge, inheritance, default reasoning, collocational relations, and even domain knowledge. With such an extension of the normal purview of "linguistic" knowledge, one may question whether there is any logical justification for distinguishing between lexical semantics and commonsense reasoning. This volume explores the question from several methodological and theoretical perspectives. What emerges is a clear consensus that the notion of the lexicon and lexical knowledge assumed in earlier linguistic research is grossly inadequate and fails to address the deeper semantic issues required for natural language analysis.
Advances in Artificial Intelligence
21st Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2008, Windsor, Canada, May 28-30, 2008. Proceedings
Häftad, Engelska, 2008
551 kr
Skickas inom 10-15 vardagar
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.