Search (175 results, page 1 of 9)

  • × theme_ss:"Wissensrepräsentation"
  1. Zeng, Q.; Yu, M.; Yu, W.; Xiong, J.; Shi, Y.; Jiang, M.: Faceted hierarchy : a new graph type to organize scientific concepts and a construction method (2019) 0.07
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    Content
    Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.
  2. Xiong, C.: Knowledge based text representations for information retrieval (2016) 0.06
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    Content
    Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Language and Information Technologies. Vgl.: https%3A%2F%2Fwww.cs.cmu.edu%2F~cx%2Fpapers%2Fknowledge_based_text_representation.pdf&usg=AOvVaw0SaTSvhWLTh__Uz_HtOtl3.
  3. Drewer, P.; Massion, F; Pulitano, D: Was haben Wissensmodellierung, Wissensstrukturierung, künstliche Intelligenz und Terminologie miteinander zu tun? (2017) 0.06
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    Abstract
    Diese Publikation beschreibt die Zusammenhänge zwischen wissenshaltigen begriffsorientierten Terminologien, Ontologien, Big Data und künstliche Intelligenz.
    Date
    13.12.2017 14:17:22
  4. Handbook on ontologies (2004) 0.05
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    BK
    54.72 / Künstliche Intelligenz
    Classification
    ST 300 Informatik / Monographien / Künstliche Intelligenz / Allgemeines
    ST 302 Informatik / Monographien / Künstliche Intelligenz / Expertensysteme; Wissensbasierte Systeme
    54.72 / Künstliche Intelligenz
    TXV (FH K)
    GHBS
    TXV (FH K)
    RVK
    ST 300 Informatik / Monographien / Künstliche Intelligenz / Allgemeines
    ST 302 Informatik / Monographien / Künstliche Intelligenz / Expertensysteme; Wissensbasierte Systeme
  5. Stojanovic, N.: Ontology-based Information Retrieval : methods and tools for cooperative query answering (2005) 0.05
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    Content
    Vgl.: http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F1627&ei=tAtYUYrBNoHKtQb3l4GYBw&usg=AFQjCNHeaxKkKU3-u54LWxMNYGXaaDLCGw&sig2=8WykXWQoDKjDSdGtAakH2Q&bvm=bv.44442042,d.Yms.
  6. Stuckenschmidt, H.: Ontologien : Konzepte, Technologien und Anwendungen (2009) 0.04
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    BK
    54.72 / Künstliche Intelligenz
    Classification
    54.72 / Künstliche Intelligenz
    TWX (FH K)
    GHBS
    TWX (FH K)
  7. Reimer, U.: Einführung in die Wissensrepräsentation : netzartige und schema-basierte Repräsentationsformate (1991) 0.04
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    Classification
    ST 304 Informatik / Monographien / Künstliche Intelligenz / Automatisches Programmieren, Deduction and theorem proving, Wissensrepräsentation
    IFQ (FH K)
    GHBS
    IFQ (FH K)
    RVK
    ST 304 Informatik / Monographien / Künstliche Intelligenz / Automatisches Programmieren, Deduction and theorem proving, Wissensrepräsentation
  8. Hüsken, P.: Informationssuche im Semantic Web : Methoden des Information Retrieval für die Wissensrepräsentation (2006) 0.04
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    BK
    54.72 / Künstliche Intelligenz
    Classification
    54.72 / Künstliche Intelligenz
    Date
    12. 2.2011 17:29:27
  9. Stuckenschmidt, H.; Harmelen, F. van: Information sharing on the semantic web (2005) 0.03
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    BK
    54.72 / Künstliche Intelligenz
    Classification
    54.72 / Künstliche Intelligenz
    TWX (FH K)
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  10. Nagao, M.: Knowledge and inference (1990) 0.03
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    Classification
    TXX (FH K)
    GHBS
    TXX (FH K)
    RSWK
    Inferenz <Künstliche Intelligenz> / Wissensrepräsentation
    Subject
    Inferenz <Künstliche Intelligenz> / Wissensrepräsentation
  11. ¬The Semantic Web - ISWC 2010 : 9th International Semantic Web Conference, ISWC 2010, Shanghai, China, November 7-11, 2010, Revised Selected Papers, Part 2. (2010) 0.03
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    BK
    54.72 / Künstliche Intelligenz
    Classification
    54.72 / Künstliche Intelligenz
    Date
    29. 7.2011 14:44:56
  12. Hermans, J.: Ontologiebasiertes Information Retrieval für das Wissensmanagement (2008) 0.03
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  13. ¬The Semantic Web - ISWC 2010 : 9th International Semantic Web Conference, ISWC 2010, Shanghai, China, November 7-11, 2010, Revised Selected Papers, Part I. (2010) 0.02
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    BK
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    Classification
    54.72 / Künstliche Intelligenz
    Date
    29. 7.2011 14:44:56
  14. Hodgson, J.P.E.: Knowledge representation and language in AI (1991) 0.02
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    54.72 / Künstliche Intelligenz
    Classification
    54.72 / Künstliche Intelligenz
    RSWK
    Wissensrepräsentation / Künstliche Intelligenz (BVB)
    Künstliche Intelligenz / Programmiersprache (BVB)
    Subject
    Wissensrepräsentation / Künstliche Intelligenz (BVB)
    Künstliche Intelligenz / Programmiersprache (BVB)
  15. Ehrig, M.; Studer, R.: Wissensvernetzung durch Ontologien (2006) 0.02
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    Abstract
    In der Informatik sind Ontologien formale Modelle eines Anwendungsbereiches, die die Kommunikation zwischen menschlichen und/oder maschinellen Akteuren unterstützen und damit den Austausch und das Teilen von Wissen in Unternehmen erleichtern. Ontologien zur strukturierten Darstellung von Wissen zu nutzen hat deshalb in den letzten Jahren zunehmende Verbreitung gefunden. Schon heute existieren weltweit tausende Ontologien. Um Interoperabilität zwischen darauf aufbauenden Softwareagenten oder Webservices zu ermöglichen, ist die semantische Integration der Ontologien eine zwingendnotwendige Vorraussetzung. Wie man sieh leicht verdeutlichen kann, ist die rein manuelle Erstellung der Abbildungen ab einer bestimmten Größe. Komplexität und Veränderungsrate der Ontologien nicht mehr ohne weiteres möglich. Automatische oder semiautomatische Technologien müssen den Nutzer darin unterstützen. Das Integrationsproblem beschäftigt Forschung und Industrie schon seit vielen Jahren z. B. im Bereich der Datenbankintegration. Neu ist jedoch die Möglichkeit komplexe semantische Informationen. wie sie in Ontologien vorhanden sind, einzubeziehen. Zur Ontologieintegration wird in diesem Kapitel ein sechsstufiger genereller Prozess basierend auf den semantischen Strukturen eingeführt. Erweiterungen beschäftigen sich mit der Effizienz oder der optimalen Nutzereinbindung in diesen Prozess. Außerdem werden zwei Anwendungen vorgestellt, in denen dieser Prozess erfolgreich umgesetzt wurde. In einem abschließenden Fazit werden neue aktuelle Trends angesprochen. Da die Ansätze prinzipiell auf jedes Schema übertragbar sind, das eine semantische Basis enthält, geht der Einsatzbereich dieser Forschung weit über reine Ontologieanwendungen hinaus.
  16. Schnurr, H.-P.: Semantisches Ratgebersystem für die Roboterwartung (2006) 0.02
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    Abstract
    Das im Folgenden dargestellte Beispiel zeigt den Einsatz eines semantischen Ratgebersystems zur Unterstützung des Kundendienstes eines Roboterherstellers. Die Optimierung von Kundendiensteinsätzen ist für viele Hersteller von komplexen Investitionsgütern ein essentieller Prozess. Semantische Technologien können helfen, gezielt Erfahrungswissen von Servicetechnikern zu erfassen und dadurch die Fehlerdiagnose am Telefon durch Rückfragen vom System zu verbessern oder den Fehler ganz zu beseitigen, Servicetechniker einzuarbeiten, sie besser auf ihren Einsatz vorzubereiten und sie vor Ort bei der Lösung von Problemen zu unterstützen
  17. Developments in applied artificial intelligence : proceedings / 16th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2003, Loughborough, UK, June 23 - 26, 2003 (2003) 0.02
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    BK
    54.72 (Künstliche Intelligenz)
    Classification
    54.72 (Künstliche Intelligenz)
    RSWK
    Künstliche Intelligenz / Kongress / Loughborough <2003>
    Subject
    Künstliche Intelligenz / Kongress / Loughborough <2003>
  18. Becker, H.-G.: MODS2FRBRoo : Ein Tool zur Anbindung von bibliografischen Daten an eine Ontologie für Begriffe und Informationen (2010) 0.02
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    Abstract
    Es wird ein Verfahren vorgestellt, mit dem bereits existierende bibliografische Daten in die CIDOC CRM/FRBRoo-Umgebung übertragen werden können. Es handelt sich dabei um einen mehrstufigen XSLT-Prozess, der im MODS-Format vorliegende bibliografische Daten in ein FRBRoo-konformes RDF umwandelt. Dazu werden die unterschiedlichen Publikationstypen in FRBRoo identifiziert und modelliert. Für die Abbildung der einzelnen bibliografischen Kategorien aus dem verwendeten Austauschformat auf die FRBRoo-Klassen wird auf Konzepte von RDA zurückgegriffen.
  19. Leidig, T.: Ontologien für die Informationsintegration in Geschäftsanwendungen (2006) 0.02
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    Abstract
    Informationsintegration auf Basis semantischer Modelle ist ein viel versprechender Ansatz zur Bewältigung des Informationsüberflusses. Informationen und Wissen stehen oft in großer Menge zur Verfügung, doch es ist sehr schwierig, das Wissen in einer spezifischen Situation zu fin-den oder überhaupt gewahr zu sein, dass adäquate Informationen vorhanden sind. Der Prozess des Suchens erfordert sehr viel Geduld und Erfahrung. Reine textuelle Suchmaschinen wie Google führen leider oft nicht oder nicht effizient genug zum Ziel. Eine zentrale Herausforderung ist daher die Filterung und strukturierte Aufbereitung von Informationen im Kontext der aktuellen Arbeitsumgebung und der jeweiligen Aufgabenstellung. Semantische Metadaten können dabei helfen, diese Abbildung vorhandener Informationsquellen in den Aufgabenkontext zu bewerkstelligen. Doch wie kommt man zu geeigneten, reichhaltigen semantischen Metadaten? Nach heutiger Praxis geschieht das hauptsächlich durch manuelle Verfahren, die allerdings auch viele Probleme aufwerfen. Daher ist der Erfolg semantischer Informationsintegration in hohem Maße davon abhängig, ob es gelingt semantische Metadaten automatisch zu extrahieren und hinreichend aktuell zu halten.
  20. Haas, M.: Methoden der künstlichen Intelligenz in betriebswirtschaftlichen Anwendungen (2006) 0.02
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