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  • × year_i:[2000 TO 2010}
  • × author_ss:"Wille, R."
  1. Wille, R.: Begriffliche Wissensverarbeitung in der Wirtschaft (2002) 0.02 
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    Abstract
    Begriffliche Wissensverarbeitung ist einem pragmatischen Wissensverständnis verpflichtet, nach dem menschliches Wissen in einem offenen Prozess menschlichen Denkens, Argumentierens und Kommunizierens entsteht und weiterlebt. Sie gründet sich auf eine mathematische Begriffstheorie, die auf das wechselseitige Zusammenwirken von Formalem und Inhaltlichem ausgerichtet ist. Wie diese theoretische Konzeption in der wirtschaftlichen Praxis zur Wirkung kommt wird erläutert anhand der Kernprozesse des organisationalen Wissensmanagements, d.h. nach G. Probst et al. anhand von Wissensidentifikation, Wissenserwerb, Wissensentwicklung, Wissens(ver)teilung, Wissensnutzung und Wissensbewahrung; jeweils an einem Beispiel wird der Einsatz spezifischer Methoden der Begrifflichen Wissensverarbeitung demonstriert. Abschließend wird auf den prozesshaften Wirkungszusammenhang von Wissenszielen und Wissensbewertungen mit den Kernprozessen aus Sicht der Begrifflichen Wissensverarbeitung eingegangen.
    Source
    Information - Wissenschaft und Praxis. 53(2002) H.3, S.149-160
  2. Rock, T.; Wille, R.: ¬Ein TOSCANA-Erkundungssystem zur Literatursuche (2000) 0.01 
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    Source
    Begriffliche Wissensverarbeitung: Methoden und Anwendungen, mit Beiträgen zahlreicher Fachwissenschaftler. Hrsg.: G. Stumme u. R. Wille
  3. Wille, R.; Zickwolff, M.: Grundlagen einer Triadischen Begriffsanalyse (2000) 0.00 
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    Source
    Begriffliche Wissensverarbeitung: Methoden und Anwendungen, mit Beiträgen zahlreicher Fachwissenschaftler. Hrsg.: G. Stumme u. R. Wille
  4. Hereth, J.; Stumme, G.; Wille, R.; Wille, U.: Conceptual knowledge discovery and data analysis (2000) 0.00 
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    Abstract
    In this paper, we discuss Conceptual Knowledge Discovery in Databases (CKDD) in its connection with Data Analysis. Our approach is based on Formal Concept Analysis, a mathematical theory which has been developed and proven useful during the last 20 years. Formal Concept Analysis has led to a theory of conceptual information systems which has been applied by using the management system TOSCANA in a wide range of domains. In this paper, we use such an application in database marketing to demonstrate how methods and procedures of CKDD can be applied in Data Analysis. In particular, we show the interplay and integration of data mining and data analysis techniques based on Formal Concept Analysis. The main concern of this paper is to explain how the transition from data to knowledge can be supported by a TOSCANA system. To clarify the transition steps we discuss their correspondence to the five levels of knowledge representation established by R. Brachman and to the steps of empirically grounded theory building proposed by A. Strauss and J. Corbin
    Series
    Lecture notes in computer science; vol.1867: Lecture notes on artificial intelligence
  5. Eklund, P.; Groh, B.; Stumme, G.; Wille, R.: ¬A conceptual-logic extension of TOSCANA (2000) 0.00 
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    Abstract
    The aim of this paper is to indicate how TOSCANA may be extended to allow graphical representations not only of concept lattices but also of concept graphs in the sense of Contextual Logic. The contextual- logic extension of TOSCANA requires the logical scaling of conceptual and relational scales for which we propose the Peircean Algebraic Logic as reconstructed by R. W. Burch. As graphical representations we recommend, besides labelled line diagrams of concept lattices and Sowa's diagrams of conceptual graphs, particular information maps for utilizing background knowledge as much as possible. Our considerations are illustrated by a small information system about the domestic flights in Austria
    Series
    Lecture notes in computer science; vol.1867: Lecture notes on artificial intelligence

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