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  • × author_ss:"Wille, R."
  • × theme_ss:"Formale Begriffsanalyse"
  1. Vogt, F.; Wille, R.: TOSCANA - a graphical tool for analyzing and exploring data (1995) 0.03 
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    Abstract
    TOSCANA is a computer program which allows an online interaction with larger data bases to analyse and explore data conceptually. It uses labelled line diagrams of concept lattices to communicate knowledge coded in given data. The basic problem to create online presentations of concept lattices is solved by composing prepared diagrams to nested line diagrams. A larger number of applications in different areas have already shown that TOSCANA is a useful tool for many purposes
    Source
    Knowledge organization. 22(1995) no.2, S.78-81
    Type
    a
  2. Wille, R.: Lattices in data analysis : how to draw them with a computer (1989) 0.00 
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  3. Ganter, B.; Stahl, J.; Wille, R.: Conceptual measurement and many-valued contexts (1986) 0.00 
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    Source
    Classification as a tool of research. Ed.: W. Gaul u. M. Schader
    Type
    a
  4. Vogt, F.; Wachter, C.; Wille, R.: Data analysis based on a conceptual file (1991) 0.00 
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  5. Vogt, F.; Wille, R.: TOSCANA - a graphical tool for analyzing and exploring data (1995) 0.00 
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  6. Luksch, P.; Wille, R.: ¬A mathematical model for conceptual knowledge systems (1991) 0.00 
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    Abstract
    Objects, attributes, and concepts are basic notations of conceptual knowledge; they are linked by the following four basic relations: an object has an attribute, an object belongs to a concept, an attribute abstracts from a concept, and a concept is a subconcept of another concept. These structural elements are well mathematized in formal concept analysis. Therefore, conceptual knowledge systems can be mathematically modelled in the frame of formal concept analysis. How such modelling may be performed is indicated by an example of a conceptual knowledge system. The formal definition of the model finally clarifies in which ways representation, inference, acquisition, and communication of conceptual knowledge can be mathematically treated
    Type
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  7. Wille, R.: Begriffliche Datensysteme als Werkzeuge der Wissenskommunikation (1992) 0.00 
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    Source
    Mensch und Maschine: Informationelle Schnittstellen der Kommunikation. Proc. des 3. Int. Symposiums für Informationswissenschaft (ISI'92), 5.-7.11.1992 in Saarbrücken. Hrsg.: H.H. Zimmermann, H.-D. Luckhardt u. A. Schulz
    Type
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  8. Rusch, A.; Wille, R.: Knowledge spaces and formal concept analysis (1996) 0.00 
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  9. Wille, R.: Line diagrams of hierarchical concept systems (1984) 0.00 
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  10. Wille, R.: Bedeutungen von Begriffsverbänden (1987) 0.00 
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  11. Wille, R.: Geometric representations of concept lattices (1989) 0.00 
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  12. Wille, R.: Concept lattices and conceptual knowledge systems (1992) 0.00 
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  13. Kipke, U.; Wille, R.: Formale Begriffsanalyse erläutert an einem Wortfeld (1987) 0.00 
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  14. Ganter, B.; Wille, R.: Conceptual scaling (1989) 0.00 
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  15. Vogt, C.; Wille, R.: Formale Begriffsanalyse : Darstellung und Analyse von bibliographischen Daten (1994) 0.00 
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  16. Wille, R.: Knowledge acquisition by methods of formal concept analysis (1989) 0.00 
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  17. Wille, R.; Zickwolff, M.: Grundlagen einer Triadischen Begriffsanalyse (2000) 0.00 
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  18. Rock, T.; Wille, R.: ¬Ein TOSCANA-Erkundungssystem zur Literatursuche (2000) 0.00 
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  19. 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
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  20. Ganter, B.; Wille, R.: Implikationen und Abhängigkeiten zwischen Merkmalen (1986) 0.00 
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