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Sinopsis
This work investigates automating the population of knowledge bases with systems of concepts extracted from texts in arbitrary domains, normally undertaken manually by domain experts. It explores issues of terminology extraction from domain texts, the need for and use of knowledge representation, and the means by which terminology extraction and knowledge representation can be combined with international standards for terminology to produce such an initial model of an arbitrary specialist domain. A method is elaborated for identifying evidence of key domain concepts, expressed through terms used in place of and in relation to these concepts. The work presented may contribute to the Semantic Web and related initiatives by helping to overcome the well-documented and unsolved AI problem of producing an initial model of an arbitrary specialist domain from background resources without significant hand-crafting effort and involvement of a domain expert: the so-called "Knowledge Acquisition Bottleneck". This bottleneck is usually only overcome through extensive and expensive interactions with domain experts, involving a number of expert interviews.
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This work investigates automating the population of knowledge bases with systems of concepts extracted from texts in arbitrary domains, normally undertaken manually by domain experts. It explores issues of terminology extraction from domain texts, the need for and use of knowledge representation, and the means by which terminology extraction and knowledge representation can be combined with international standards for terminology to produce such an initial model of an arbitrary specialist domain. A method is elaborated for identifying evidence of key domain concepts, expressed through terms used in place of and in relation to these concepts. The work presented may contribute to the Semantic Web and related initiatives by helping to overcome the well-documented and unsolved AI problem of producing an initial model of an arbitrary specialist domain from background resources without significant hand-crafting effort and involvement of a domain expert: the so-called "Knowledge Acquisition Bottleneck". This bottleneck is usually only overcome through extensive and expensive interactions with domain experts, involving a number of expert interviews.
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Extracting Systems of Concepts from Text
Publicado por
LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838355105
ISBN 13: 9783838355108
Nuevo
Tapa blanda
Librería: moluna, Greven, Alemania
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Gillam LeeDr Lee Gillam MBCS CITP FHEA: Lecturer at the University of Surrey, and a Director of GeoLang Ltd.This work investigates automating the population of knowledge bases with systems of concepts extracted from texts in arbi. Nº de ref. del artículo: 5415900
Cantidad disponible: Más de 20 disponibles
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Extracting Systems of Concepts from Text
Publicado por
LAP LAMBERT Academic Publishing Apr 2010, 2010
ISBN 10: 3838355105
ISBN 13: 9783838355108
Nuevo
Taschenbuch
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This work investigates automating the population of knowledge bases with systems of concepts extracted from texts in arbitrary domains, normally undertaken manually by domain experts. It explores issues of terminology extraction from domain texts, the need for and use of knowledge representation, and the means by which terminology extraction and knowledge representation can be combined with international standards for terminology to produce such an initial model of an arbitrary specialist domain. A method is elaborated for identifying evidence of key domain concepts, expressed through terms used in place of and in relation to these concepts. The work presented may contribute to the Semantic Web and related initiatives by helping to overcome the well-documented and unsolved AI problem of producing an initial model of an arbitrary specialist domain from background resources without significant hand-crafting effort and involvement of a domain expert: the so-called 'Knowledge Acquisition Bottleneck'. This bottleneck is usually only overcome through extensive and expensive interactions with domain experts, involving a number of expert interviews. 196 pp. Englisch. Nº de ref. del artículo: 9783838355108
Cantidad disponible: 2 disponibles
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Extracting Systems of Concepts from Text : Automatically Learning Ontologies
Publicado por
LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838355105
ISBN 13: 9783838355108
Nuevo
Taschenbuch
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This work investigates automating the population of knowledge bases with systems of concepts extracted from texts in arbitrary domains, normally undertaken manually by domain experts. It explores issues of terminology extraction from domain texts, the need for and use of knowledge representation, and the means by which terminology extraction and knowledge representation can be combined with international standards for terminology to produce such an initial model of an arbitrary specialist domain. A method is elaborated for identifying evidence of key domain concepts, expressed through terms used in place of and in relation to these concepts. The work presented may contribute to the Semantic Web and related initiatives by helping to overcome the well-documented and unsolved AI problem of producing an initial model of an arbitrary specialist domain from background resources without significant hand-crafting effort and involvement of a domain expert: the so-called 'Knowledge Acquisition Bottleneck'. This bottleneck is usually only overcome through extensive and expensive interactions with domain experts, involving a number of expert interviews. Nº de ref. del artículo: 9783838355108
Cantidad disponible: 1 disponibles
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Extracting Systems of Concepts from Text
Publicado por
LAP LAMBERT Academic Publishing Apr 2010, 2010
ISBN 10: 3838355105
ISBN 13: 9783838355108
Nuevo
Taschenbuch
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. Neuware -This work investigates automating the population of knowledge bases with systems of concepts extracted from texts in arbitrary domains, normally undertaken manually by domain experts. It explores issues of terminology extraction from domain texts, the need for and use of knowledge representation, and the means by which terminology extraction and knowledge representation can be combined with international standards for terminology to produce such an initial model of an arbitrary specialist domain. A method is elaborated for identifying evidence of key domain concepts, expressed through terms used in place of and in relation to these concepts. The work presented may contribute to the Semantic Web and related initiatives by helping to overcome the well-documented and unsolved AI problem of producing an initial model of an arbitrary specialist domain from background resources without significant hand-crafting effort and involvement of a domain expert: the so-called 'Knowledge Acquisition Bottleneck'. This bottleneck is usually only overcome through extensive and expensive interactions with domain experts, involving a number of expert interviews.Books on Demand GmbH, Überseering 33, 22297 Hamburg 196 pp. Englisch. Nº de ref. del artículo: 9783838355108
Cantidad disponible: 2 disponibles
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Extracting Systems of Concepts from Text: Automatically Learning Ontologies
Publicado por
LAP Lambert Academic Publishing, 2010
ISBN 10: 3838355105
ISBN 13: 9783838355108
Antiguo o usado
Paperback
Librería: Mispah books, Redhill, SURRE, Reino Unido
Calificación del vendedor: 4 de 5 estrellas
Paperback. Condición: Like New. Like New. book. Nº de ref. del artículo: ERICA78738383551056
Cantidad disponible: 1 disponibles