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  • × theme_ss:"Formale Begriffsanalyse"
  1. Helmerich, M.: Liniendiagramme in der Wissenskommunikation : eine mathematisch-didaktische Untersuchung (2011) 0.01 
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    Abstract
    Die Kommunikation von Wissen nimmt in der modernen Wissensgesellschaft einen entscheidenden Stellenwert ein. Kommunikation im Habermas'schen Sinne eines intersubjektiven Verständigungsprozesses ist dann aber auch mehr als nur der Austausch von Zeichen: es geht um Sinn und Bedeutung und die Aushandlungsprozesse darüber, wie wir als Kommunikationsgemeinschaft Zeichen interpretieren und darin Informationen codieren. Als Medium für solche Kommunikations - prozesse eignen sich besonders gut Liniendiagramme aus der Theorie der Formalen Begriffsanalyse. Diese Liniendiagramme sind nicht nur geeignet, die Wissenskommunikation zu unterstützen, sondern auch Kommunikationsprozesse überhaupt erst zu initiieren. Solche Liniendiagramme können die Wissenskommunikation gut unterstützen, da sie durch ihre Einfachheit, Ordnung, Prägnanz und ergänzende Stimulanz für Verständigung über die wissensgenerierende Information sorgen. Außerdem wird mit den Liniendiagrammen ein Kommunikationsmittel bereitgestellt, dass inter- und transdisziplinär wirksam werden kann und so Wissensgebiete für verschiedene Disziplinen erschließt, da es mit den Diagrammen gelingt, die allgemeine, zugrundeliegende logische Struktur mit Hilfe eines mathematisch fundierten Verfahrens herauszuarbeiten. Liniendiagramme stellen nicht nur Wissensgebiete in einer geordneten, strukturierten Form dar, sondern verwenden dafür auch formale Begriffe und knüpfen damit an Begriffe als Objekte des menschlichen Denkens an. In den Begriffe verschmilzt ein Ausschnitt der betrachteten Objekte (im Beispiel die verschiedenen Gewässerarten) mit den ihnen gemeinsamen Merkmalen zu neuen Denkeinheiten und geben somit dem Wissen eine Form, in der Kommunikation über diese Denkeinheiten und die darin konzentrierte Information ermöglicht wird.
  2. Prediger, S.: Kontextuelle Urteilslogik mit Begriffsgraphen : Ein Beitrag zur Restrukturierung der mathematischen Logik (1998) 0.01 
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    Date
    26. 2.2008 15:58:22
  3. Wille, R.: Lattices in data analysis : how to draw them with a computer (1989) 0.00 
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    Type
    a
  4. 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
  5. Vogt, F.; Wachter, C.; Wille, R.: Data analysis based on a conceptual file (1991) 0.00 
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  6. Vogt, F.; Wille, R.: TOSCANA - a graphical tool for analyzing and exploring data (1995) 0.00 
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  7. Lex, W.: ¬A representation of concepts for their computerization (1987) 0.00 
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    Abstract
    A lattice theoretical description of concept hierarchies is developed using for attributes the terms "given", "negated", "open" and "impossible" as the truth-values of a four-valued logic. Similar to the theory of B. Ganter and R. Wille so does this framework permit a precise representation of the usual interdependences in a field of related concepts - such as superconcepts, subconcept, contrary concepts etc. -, whenever the concepts under consideration can be sufficiently described by the presence or absence of certain attributes ...
    Type
    a
  8. 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
    a
  9. Priss, U.: Lattice-based information retrieval (2000) 0.00 
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    Abstract
    A lattice-based model for information retrieval was suggested in the 1960's but has been seen as a theoretical possibility hard to practically apply ever since. This paper attempts to revive the lattice model and demonstrate its applicability in an information retrieval system, FalR, that incorporates a graphical representation of a faceted thesaurus. It shows how Boolean queries can be lattice-theoretically related to the concepts of the thesaurus and visualized within the thesaurus display. An advantage of FaIR is that it allows for a high level of transparency of the system, which can be controlled by the user
    Type
    a
  10. Priss, U.: ¬A graphical interface for conceptually navigating faceted thesauri (1998) 0.00 
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    Abstract
    This paper describes a graphical interface for the navigation and construction of faceted thesauri that is based on formal concept analysis. Each facet of a thesaurus is represented as a mathematical lattice that is further subdivided into components. Users can graphically navigate through the Java implementation of the interface by clicking on terms that connect facets and components. Since there are many applications for thesauri in the knowledge representation field, such a graphical interface has the potential of being very useful
    Type
    a
  11. 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
    a
  12. Skorsky, M.: How to draw a concept lattice with parallelograms (1989) 0.00 
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  13. Rusch, A.; Wille, R.: Knowledge spaces and formal concept analysis (1996) 0.00 
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  14. Ganter, B.: Algorithmen zur formalen Begriffsanalyse (1991) 0.00 
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  15. Wille, R.: Geometric representations of concept lattices (1989) 0.00 
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  16. Wille, R.: Concept lattices and conceptual knowledge systems (1992) 0.00 
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  17. Priss, U.: Formal concept analysis in information science (2006) 0.00 
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  18. Sedelow, W.A.: ¬The formal analysis of concepts (1993) 0.00 
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    Abstract
    The present paper focuses on the extraction, by means of a formal logical/mathematical methodology (i.e. automatically, exclusively by rule), of concept content, as in, for example, continuous discourse. The approach to a fully formal defintion of concept content ultimately is owing to a German government initiative to establish 'standards' regarding concepts, in conjunction with efforts to stipulate precisely (and then, derivatively, through computer prgrams) data and information needs according to work role in certain government offices
    Type
    a
  19. Kipke, U.; Wille, R.: Formale Begriffsanalyse erläutert an einem Wortfeld (1987) 0.00 
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  20. De Maio, C.; Fenza, G.; Loia, V.; Senatore, S.: Hierarchical web resources retrieval by exploiting Fuzzy Formal Concept Analysis (2012) 0.00 
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    Abstract
    In recent years, knowledge structuring is assuming important roles in several real world applications such as decision support, cooperative problem solving, e-commerce, Semantic Web and, even in planning systems. Ontologies play an important role in supporting automated processes to access information and are at the core of new strategies for the development of knowledge-based systems. Yet, developing an ontology is a time-consuming task which often needs an accurate domain expertise to tackle structural and logical difficulties in the definition of concepts as well as conceivable relationships. This work presents an ontology-based retrieval approach, that supports data organization and visualization and provides a friendly navigation model. It exploits the fuzzy extension of the Formal Concept Analysis theory to elicit conceptualizations from datasets and generate a hierarchy-based representation of extracted knowledge. An intuitive graphical interface provides a multi-facets view of the built ontology. Through a transparent query-based retrieval, final users navigate across concepts, relations and population.
    Type
    a

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