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  • × theme_ss:"Case Based Reasoning"
  • × type_ss:"a"
  1. Pfeffer, M.: Automatische Vergabe von RVK-Notationen mittels fallbasiertem Schließen (2009) 0.01
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    Abstract
    Klassifikation von bibliografischen Einheiten ist für einen systematischen Zugang zu den Beständen einer Bibliothek und deren Aufstellung unumgänglich. Bislang wurde diese Aufgabe von Fachexperten manuell erledigt, sei es individuell nach einer selbst entwickelten Systematik oder kooperativ nach einer gemeinsamen Systematik. In dieser Arbeit wird ein Verfahren zur Automatisierung des Klassifikationsvorgangs vorgestellt. Dabei kommt das Verfahren des fallbasierten Schließens zum Einsatz, das im Kontext der Forschung zur künstlichen Intelligenz entwickelt wurde. Das Verfahren liefert für jedes Werk, für das bibliografische Daten vorliegen, eine oder mehrere mögliche Klassifikationen. In Experimenten werden die Ergebnisse der automatischen Klassifikation mit der durch Fachexperten verglichen. Diese Experimente belegen die hohe Qualität der automatischen Klassifikation und dass das Verfahren geeignet ist, Fachexperten bei der Klassifikationsarbeit signifikant zu entlasten. Auch die nahezu vollständige Resystematisierung eines Bibliothekskataloges ist - mit gewissen Abstrichen - möglich.
    Date
    22. 8.2009 19:51:28
    Source
    Wissen bewegen - Bibliotheken in der Informationsgesellschaft / 97. Deutscher Bibliothekartag in Mannheim, 2008. Hrsg. von Ulrich Hohoff und Per Knudsen. Bearb. von Stefan Siebert
  2. Czap, H.: Einführung in Wissensorganisation und Case-Based Reasoning (1996) 0.00
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    Abstract
    CBR ist eng gekoppelt mit Lernen, verstanden als Anreicherung von Wissen. Wissen wird unterteilt in Faktenwissen und Handhabungs-/Orientierungswissen. Letzteres verfügbar zu haben wird als primäres Ziel von Lernen und damit auch von CBR herausgearbeitet. Die Übertragbarkeitsproblematik, d.h. die Nutzung von gespeichertem Erfahrungswissen (alte Fälle und ihre Lösungen) zur Lösung neuer Problemstellungen wird an einem eingängigen Beispiel (Dunckers Bestrahlungsproblem illustriert). Abschließend wird der CBR-Zyklus kurz vorgestellt
  3. Coulon, C.-H.: ¬Die Rolle des Anpassungswissens im CBR : am Beispiel der Ausnutzung von Struktur im CBR (1996) 0.00
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    Abstract
    Ein wesentlicher Vorteil des CBR im Vergleich zu generativen Ansätzen ist ein geringer Bedarf an das zu formalisierende Wissen. Insbesondere ist es möglich trotz unvollständigen Anpassungswissens vollständige Lösungen zu finden. Dieser Beitrag beschreibt, wodurch sich Anpassungswissen von Regelwissen unterscheidet und wieviel Anpassungswissen man unbedingt benötigt. Die Leistungsfähigkeit eines wissensarmen CBR-Ansatzes wird am Beispiel der Anpassung toplogischer Strukturen diskutiert
  4. Mazzucchelli, A.; Sartori , F.: String similarity in CBR platforms : a preliminary study (2014) 0.00
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    Pages
    S.22-29
    Source
    Metadata and semantics research: 8th Research Conference, MTSR 2014, Karlsruhe, Germany, November 27-29, 2014, Proceedings. Eds.: S. Closs et al
  5. Chen, Z.: ¬A conceptual model for storage and retrieval of short scientific texts (1993) 0.00
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    Source
    Information processing and management. 29(1993) no.2, S.209-214
  6. Mataras, R.L.D.; Plaza, E.: Case-based reasoning : an overview (1997) 0.00
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    Source
    AI communications. 10(1997) no.1, S.21-29
  7. Mahapatra, R.; Sen, A.: Case base management systems : providing database support to case-based reasoners (1994) 0.00
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    Source
    Journal of database management. 5(1994) no.2, S.19-29
  8. Golding, A.R.; Rosenbloom, P.S.: Improving accuracy by combining rule-based and case-based reasoning (1996) 0.00
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    Date
    6. 3.1997 16:22:15
  9. Ram, A.; Santamaria, J.C.: Continuous case-based reasoning (1997) 0.00
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    Date
    6. 3.1997 16:22:15
  10. Kohno, T.: Error repair and knowledge acquisition via case-based reasoning (1997) 0.00
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    Date
    6. 3.1997 16:22:15
  11. Akerele, O.; David, A.; Osofisan, A.: Using the concepts of Case Based Reasoning and Basic Categories for enhancing adaptation to the user's level of knowledge in Decision Support System (2014) 0.00
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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