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Knowledge Representation and the Semantics of Natural Language / by Hermann Helbig ; edited by Dov M. Gabbay, Jörg Siekmann.

Por: Colaborador(es): Tipo de material: TextoTextoSeries Cognitive TechnologiesEditor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2006Descripción: xIx, 646 páginas 258 ilustraciones, With CD-ROM. recurso en líneaTipo de contenido:
  • texto
Tipo de medio:
  • computadora
Tipo de portador:
  • recurso en línea
ISBN:
  • 9783540299660
Formatos físicos adicionales: Edición impresa:: Sin títuloClasificación LoC:
  • P98-98.5
Recursos en línea:
Contenidos:
Knowledge Representation with MultiNet -- Historical Roots -- Basic Concepts -- Semantic Characterization of Objects -- Semantic Characterization of Situations -- The Comparison of Entities -- The Spatio-temporal Characterization of Entities -- Modality and Negation -- Quantification and Pluralities -- The Role of Layer Information in Semantic Representations -- Relations Between Situations -- Lexicon and Knowledge Representation -- Question Answering and Inferences -- Software Tools for the Knowledge Engineer and Sample Applications -- Comparison Between MultiNet and Other Semantic Formalisms or Knowledge Representation Paradigms -- The Representational Means of MultiNet -- Overview and Representational Principles -- Means for Expressing Classification and Stratification -- Relational and Functional Means of Representation.
Resumen: The book presents an interdisciplinary approach to knowledge representation and the treatment of semantic phenomena of natural language, which is positioned between artificial intelligence, computational linguistics, and cognitive psychology. The proposed method is based on Multilayered Extended Semantic Networks (MultiNets), which can be used for theoretical investigations into the semantics of natural language, for cognitive modeling, for describing lexical entries in a computational lexicon, and for natural language processing (NLP). Part I deals with fundamental problems of semantic knowledge representation and semantic interpretation of natural language phenomena. Part II provides a systematic description of the representational means of MultiNet, one of the most comprehensive and thoroughly specified collections of relations and functions used in real NLP applications. MultiNet is embedded into a system of software tools comprising a workbench for the knowledge engineer, a semantic interpreter translating natural language expressions into formal meaning structures, and a workbench for the computer lexicographer. The book has been used for courses in artificial intelligence at several universities and is one of the cornerstones for teaching computational linguistics in a virtual electronic laboratory.
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Springer eBooks

Knowledge Representation with MultiNet -- Historical Roots -- Basic Concepts -- Semantic Characterization of Objects -- Semantic Characterization of Situations -- The Comparison of Entities -- The Spatio-temporal Characterization of Entities -- Modality and Negation -- Quantification and Pluralities -- The Role of Layer Information in Semantic Representations -- Relations Between Situations -- Lexicon and Knowledge Representation -- Question Answering and Inferences -- Software Tools for the Knowledge Engineer and Sample Applications -- Comparison Between MultiNet and Other Semantic Formalisms or Knowledge Representation Paradigms -- The Representational Means of MultiNet -- Overview and Representational Principles -- Means for Expressing Classification and Stratification -- Relational and Functional Means of Representation.

The book presents an interdisciplinary approach to knowledge representation and the treatment of semantic phenomena of natural language, which is positioned between artificial intelligence, computational linguistics, and cognitive psychology. The proposed method is based on Multilayered Extended Semantic Networks (MultiNets), which can be used for theoretical investigations into the semantics of natural language, for cognitive modeling, for describing lexical entries in a computational lexicon, and for natural language processing (NLP). Part I deals with fundamental problems of semantic knowledge representation and semantic interpretation of natural language phenomena. Part II provides a systematic description of the representational means of MultiNet, one of the most comprehensive and thoroughly specified collections of relations and functions used in real NLP applications. MultiNet is embedded into a system of software tools comprising a workbench for the knowledge engineer, a semantic interpreter translating natural language expressions into formal meaning structures, and a workbench for the computer lexicographer. The book has been used for courses in artificial intelligence at several universities and is one of the cornerstones for teaching computational linguistics in a virtual electronic laboratory.

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