Stammdaten

Titel: Configuration Knowledge Representations for Semantic Web Applications
Untertitel:
Kurzfassung: Today’s economy exhibits a growing trend towards highly specialized solution providers cooperatively offering configurable products and services to their customers. This paradigm shift requires the extension of current standalone configuration technology with capabilities of knowledge sharing and distributed problem solving. In this context a standardized configuration knowledge representation language with formal semantics is needed in order to support knowledge interchange between different configuration environments. OIL and DAML+OIL are based on such formal semantics (description logic) and are very popular for knowledge representation in the Semantic Web. In this paper we analyze the applicability of those languages with respect to configuration knowledge representation and discuss additional demands on expressivity. For joint configuration problem solving it is necessary to agree on a common problem definition. Therefore we give a description logic based definition of a configuration problem and show its equivalence with existing consistency based definitions thus joining the two major streams in knowledge based configuration (description logics and predicate logic/constraint based configuration).
Schlagworte:
Publikationstyp: Beitrag in Zeitschrift (Autorenschaft)
Erscheinungsdatum: 04.2003 (Print)
Erschienen in: Artificial Intelligence in Engineering, Design, Analysis and Manufacturing (AI EDAM), Special Issue on Configuration
Artificial Intelligence in Engineering, Design, Analysis and Manufacturing (AI EDAM), Special Issue on Configuration
zur Publikation
 ( )
Titel der Serie: -
Bandnummer: 17
Heftnummer: 17
Erstveröffentlichung: Ja
Seite: S. 31 - 50

Versionen

Keine Version vorhanden
Erscheinungsdatum: 04.2003
ISBN: -
ISSN: 0890-0604
Homepage: -

Zuordnung

Organisation Adresse
Fakultät für Technische Wissenschaften
 
Institut für Artificial Intelligence und Cybersecurity
Universitätsstr. 65-67
A-9020 Klagenfurt
Österreich
  -993705
   aics-office@aau.at
https://www.aau.at/en/aics/
zur Organisation
Universitätsstr. 65-67
AT - A-9020  Klagenfurt

Kategorisierung

Sachgebiete Kein Sachgebiet ausgewählt
Forschungscluster Kein Forschungscluster ausgewählt
Zitationsindex
  • n.a.
Informationen zum Zitationsindex: Master Journal List
Peer Reviewed
  • Ja
Publikationsfokus
  • Science to Science (Qualitätsindikator: n.a.)
Klassifikationsraster der zugeordneten Organisationseinheiten:
Arbeitsgruppen Keine Arbeitsgruppe ausgewählt

Kooperationen

Keine Partnerorganisation ausgewählt

Beiträge der Publikation

Keine verknüpften Publikationen vorhanden