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  • × theme_ss:"Wissensrepräsentation"
  1. Järvelin, K.; Kristensen, J.; Niemi, T.; Sormunen, E.; Keskustalo, H.: ¬A deductive data model for query expansion (1996) 0.01
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    Source
    Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR '96), Zürich, Switzerland, August 18-22, 1996. Eds.: H.P. Frei et al
  2. Erbarth, M.: Wissensrepräsentation mit semantischen Netzen : Grundlagen mit einem Anwendungsbeispiel für das Multi-Channel-Publishing (2006) 0.01
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    BK
    54.72 / Künstliche Intelligenz
    Classification
    54.72 / Künstliche Intelligenz
  3. ¬The Semantic Web - ISWC 2010 : 9th International Semantic Web Conference, ISWC 2010, Shanghai, China, November 7-11, 2010, Revised Selected Papers, Part 2. (2010) 0.01
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    BK
    54.72 / Künstliche Intelligenz
    Classification
    54.72 / Künstliche Intelligenz
  4. Helbig, H.: Knowledge representation and the semantics of natural language (2014) 0.01
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    BK
    54.72 (Künstliche Intelligenz)
    Classification
    54.72 (Künstliche Intelligenz)
  5. Mahesh, K.: Highly expressive tagging for knowledge organization in the 21st century (2014) 0.01
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    Source
    Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
  6. Semantic digital libraries (2009) 0.01
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    BK
    54.72 / Künstliche Intelligenz
    Classification
    54.72 / Künstliche Intelligenz
  7. Beierle, C.; Kern-Isberner, G.: Methoden wissensbasierter Systeme : Grundlagen, Algorithmen, Anwendungen (2008) 0.01
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    BK
    54.72 / Künstliche Intelligenz
    Classification
    54.72 / Künstliche Intelligenz
  8. ¬The Semantic Web - ISWC 2010 : 9th International Semantic Web Conference, ISWC 2010, Shanghai, China, November 7-11, 2010, Revised Selected Papers, Part I. (2010) 0.01
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    BK
    54.72 / Künstliche Intelligenz
    Classification
    54.72 / Künstliche Intelligenz
  9. Helbig, H.: Wissensverarbeitung und die Semantik der natürlichen Sprache : Wissensrepräsentation mit MultiNet (2008) 0.01
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    Abstract
    Das Buch gibt eine umfassende Darstellung einer Methodik zur Interpretation und Bedeutungsrepräsentation natürlichsprachlicher Ausdrücke. Diese Methodik der "Mehrschichtigen Erweiterten Semantischen Netze", das sogenannte MultiNet-Paradigma, ist sowohl für theoretische Untersuchungen als auch für die automatische Verarbeitung natürlicher Sprache auf dem Rechner geeignet. Im ersten Teil des zweiteiligen Buches werden grundlegende Probleme der semantischen Repräsentation von Wissen bzw. der semantischen Interpretation natürlichsprachlicher Phänomene behandelt. Der zweite Teil enthält eine systematische Zusammenstellung des gesamten Repertoires von Darstellungsmitteln, die jeweils nach einem einheitlichen Schema beschrieben werden. Er dient als Kompendium der im Buch verwendeten formalen Beschreibungsmittel von MultiNet. Die vorgestellten Ergebnisse sind eingebettet in ein System von Software-Werkzeugen, die eine praktische Nutzung der MultiNet-Darstellungsmittel als Formalismus zur Bedeutungsrepräsentation im Rahmen der automatischen Sprachverarbeitung sichern. Hierzu gehören: eine Werkbank für den Wissensingenieur, ein Übersetzungssystem zur automatischen Gewinnung von Bedeutungsdarstellungen natürlichsprachlicher Sätze und eine Werkbank für den Computerlexikographen. Der Inhalt des Buches beruht auf jahrzehntelanger Forschung auf dem Gebiet der automatischen Sprachverarbeitung und wurde mit Vorlesungen zur Künstlichen Intelligenz und Wissensverarbeitung an der TU Dresden und der FernUniversität Hagen wiederholt in der Hochschullehre eingesetzt. Als Vorkenntnisse werden beim Leser lediglich Grundlagen der traditionellen Grammatik und elementare Kenntnisse der Prädikatenlogik vorausgesetzt.
  10. Stuart, D.: Practical ontologies for information professionals (2016) 0.01
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    BK
    54.72 (Künstliche Intelligenz)
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    54.72 (Künstliche Intelligenz)
  11. Schmitz-Esser, W.: Language of general communication and concept compatibility (1996) 0.01
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    Pages
    S.11-22
  12. Tudhope, D.; Hodge, G.: Terminology registries (2007) 0.01
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    Date
    26.12.2011 13:22:07
  13. Haller, S.H.M.: Mappingverfahren zur Wissensorganisation (2002) 0.01
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    Date
    30. 5.2010 16:22:35
  14. Nielsen, M.: Neuronale Netze : Alpha Go - Computer lernen Intuition (2018) 0.01
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    Source
    Spektrum der Wissenschaft. 2018, H.1, S.22-27
  15. Hinkelmann, K.: Ontopia Omnigator : ein Werkzeug zur Einführung in Topic Maps (20xx) 0.01
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  16. Haenelt, K.: Semantik im Wiki : am Beispiel des MediaWiki und Semantic MediaWiki (2011) 0.01
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  17. Weller, K.: Kooperativer Ontologieaufbau (2006) 0.01
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  18. Weller, K.: Kooperativer Ontologieaufbau (2006) 0.01
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  19. Stollberg, M.: Ontologiebasierte Wissensmodellierung : Verwendung als semantischer Grundbaustein des Semantic Web (2002) 0.01
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    Abstract
    In Kapitel A werden die Grundlagen von Ontologien als Verfahren der Wissensmodellierung erarbeitet. Dazu wird zunächst die definitorische Erfassung von Ontologien erläutert. Zur Erlangung eines fundierten Verständnisses von Wissensmodellierung und der Besonderheiten ontologiebasierter Verfahren ist die Eingliederung dieser in den relevanten wissenschaftlichen Kontext erforderlich. Die in diesem Zusammenhang betrachtete Art der Wissensmodellierung dient vornehmlich als konzeptionelle Grundlage für die Erstellung wissensverarbeitender Computersysteme. Die Entwicklung derartiger Systeme ist das Hauptanliegen der Künstlichen Intelligenz, weshalb eine Positionierung ontologiebasierter Verfahren in derselben vorgenommen wird. Dabei sind vor allem jene Ansätze interessant, auf denen ontologiebasierte Verfahren aufbauen. Zunächst werden daher die grundlegenden theoretischen Aspekte der Wissensrepräsentation erläutert und anschließend daran die Bedeutung von Ontologien im Knowledge Engineering aufgezeigt, um den Verwendungskontext derartiger Verfahren der Wissensmodellierung zu verdeutlichen. Aufbauend darauf werden die spezifischen Eigenschaften ontologiebasierter Verfahren der Wissensmodellierung erörtert, wodurch ein grundlegendes Verständnis dieser Methodik erreicht werden soll.
  20. Hitzler, P.; Janowicz, K.: Ontologies in a data driven world : finding the middle ground (2013) 0.01
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                  3.569778 = idf(docFreq=3384, maxDocs=44218)
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Years

Languages

  • e 89
  • d 31

Types

  • a 75
  • el 25
  • m 25
  • s 8
  • x 8
  • r 2
  • n 1
  • p 1
  • More… Less…

Subjects

Classifications