9783838355108 - extracting systems of concepts from text: automatically learning ontologies di gillam, lee (6 risultati)

- Brossura
Da: preigu, Osnabrück, Germaniapreigu
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 58,00
EUR 70,00 spedizioneSpedito da Germania a U.S.A.Quantità: 5 disponibili
Taschenbuch. Condizione: Neu. Extracting Systems of Concepts from Text | Automatically Learning Ontologies | Lee Gillam | Taschenbuch | 196 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838355108 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu…[dot]de | Anbieter: preigu.

- Brossura
Da: Mispah books, Redhill, SURRE, Regno UnitoMispah books
Contatta il venditoreVenditore con 4 stelleCondizione: Usato - Come nuovo
EUR 157,45
EUR 29,40 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

- Brossura
- Print on Demand
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 68,00
EUR 23,00 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: 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 fr…om 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.

- Brossura
- Print on Demand
Da: moluna, Greven, Germaniamoluna
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 55,21
EUR 48,99 spedizioneSpedito da Germania a U.S.A.Quantità: Più di 20 disponibili
Condizione: 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.

- Brossura
- Print on Demand
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 68,00
EUR 61,55 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: 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 do…main 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.

- Brossura
- Print on Demand
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 68,00
EUR 60,00 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. 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 d…omain 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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 196 pp. Englisch.