Search (15 results, page 1 of 1)

  • × theme_ss:"Formale Begriffsanalyse"
  • × type_ss:"a"
  • × year_i:[2000 TO 2010}
  1. Priss, U.: Faceted information representation (2000) 0.02 
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    Abstract
    This paper presents an abstract formalization of the notion of "facets". Facets are relational structures of units, relations and other facets selected for a certain purpose. Facets can be used to structure large knowledge representation systems into a hierarchical arrangement of consistent and independent subsystems (facets) that facilitate flexibility and combinations of different viewpoints or aspects. This paper describes the basic notions, facet characteristics and construction mechanisms. It then explicates the theory in an example of a faceted information retrieval system (FaIR)
    Date
    22. 1.2016 17:47:06
  2. Burmeister, P.; Holzer, R.: On the treatment of incomplete knowledge in formal concept analysis (2000) 0.01 
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    Abstract
    Some possible treatments of incomplete knowledge in conceptual data representation, data analysis and knowledge acquisition are presented. In particular, some ways of conceptual scalings as well as the role of the three-valued KLEENE-logic are briefly investigated. This logic is also one background in attribute exploration, a conceptual tool for knowledge acquisition. For this method a strategy is given to obtain as much of (attribute) implicational knowledge about a given "universe" as possible; and we show how to represent incomplete knowledge in order to be able to pin down the questions still to be answered in order to obtain complete knowledge in this situation
    Series
    Lecture notes in computer science; vol.1867: Lecture notes on artificial intelligence
  3. Priss, U.: Formal concept analysis in information science (2006) 0.01 
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  4. Hereth, J.; Stumme, G.; Wille, R.; Wille, U.: Conceptual knowledge discovery and data analysis (2000) 0.01 
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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. Lengnink, K.: Ähnlichkeit als Distanz in Begriffsverbänden (2000) 0.00 
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  6. Prediger, S.: Terminologische Merkmalslogik in der Formalen Begriffsanalyse (2000) 0.00 
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  7. Priss, U.: Comparing classification systems using facets (2000) 0.00 
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    Abstract
    This paper describes a qualitative methodology for comparing and analyzing classification schemes. Theoretical facets are modeled as concept lattices in the sense of formal concept analysis and are used as 'ground' on which the underlying conceptual facets of a classification scheme are visually represented as 'figures'.
    Series
    Advances in knowledge organization; vol.7
    Source
    Dynamism and stability in knowledge organization: Proceedings of the 6th International ISKO-Conference, 10-13 July 2000, Toronto, Canada. Ed.: C. Beghtol et al
  8. Ganter, B.: Computing with conceptual structures (2000) 0.00 
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    Abstract
    We give an overview over the computational tools for conceptional structures that have emerged from the theory of Formal Concept Analysis, with emphasis on basic ideas rather than technical details. We describe what we mean by conceptual computations, and try to convince the reader that an elaborate formalization is a necessary precondition. Claiming that Formal Concept Analysis provides such a formal background, we present as examples two well known algorithms in very simple pseudo code. These earl be used for navigating in a lattice, thereby supporting some prototypical tasks of conceptual computation. We refer to some of the many more advanced methods, discuss how to compute with limited precision and explain why in the case of incomplete knowledge the conceptual approach is more efficient than a combinatorial one. Utilizing this efficiency requires skillful use of the formalism. We present two results that lead in this direction
    Series
    Lecture notes in computer science; vol.1867: Lecture notes on artificial intelligence
  9. Wille, R.: Begriffliche Wissensverarbeitung in der Wirtschaft (2002) 0.00 
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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.
  10. Kohler-Koch, B.; Vogt, F.: Normen- und regelgeleitete internationale Kooperationen : Formale Begriffsanalyse in der Politikwissenschaft (2000) 0.00 
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  11. Bartel, H.-G.: Über Möglichkeiten der Formalen Begriffsanalyse in der Mathematischen Archäochemie (2000) 0.00 
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  12. 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
  13. Eklund. P.W.: Logic-based networks : concept graphs and conceptual structures (2000) 0.00 
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    Abstract
    Logic-based networks are semantic networks that support reasoning capabilities. In this paper, knowledge processing within logicbased networks is viewed as three stages. The first stage involves the formation of concepts and relations: the basic primitives with which we wish to formulate knowledge. The second stage involves the formation of wellformed formulas that express knowledge about the primitive concepts and relations once isolated. The final stage involves efficiently processing the wffs to the desired end. Our research involves each of these steps as they relate to Sowa's conceptual structures and Wille's concept lattices. Formal Concept Analysis gives us a capability to perform concept formation via symbolic machine learning. Concept(ual) Graphs provide a means to describe relational properties between primitive concept and relation types. Finally, techniques from other areas of computer science are required to compute logic-based networks efficiently. This paper illustrates the three stages of knowledge processing in practical terms using examples from our research
    Series
    Lecture notes in computer science; vol.1867: Lecture notes on artificial intelligence
  14. 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
  15. Carpineto, C.; Romano, G.: Order-theoretical ranking (2000) 0.00 
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    Abstract
    Current best-match ranking (BMR) systems perform well but cannot handle word mismatch between a query and a document. The best known alternative ranking method, hierarchical clustering-based ranking (HCR), seems to be more robust than BMR with respect to this problem, but it is hampered by theoretical and practical limitations. We present an approach to document ranking that explicitly addresses the word mismatch problem by exploiting interdocument similarity information in a novel way. Document ranking is seen as a query-document transformation driven by a conceptual representation of the whole document collection, into which the query is merged. Our approach is nased on the theory of concept (or Galois) lattices, which, er argue, provides a powerful, well-founded, and conputationally-tractable framework to model the space in which documents and query are represented and to compute such a transformation. We compared information retrieval using concept lattice-based ranking (CLR) to BMR and HCR. The results showed that HCR was outperformed by CLR as well as BMR, and suggested that, of the two best methods, BMR achieved better performance than CLR on the whole document set, whereas CLR compared more favorably when only the first retrieved documents were used for evaluation. We also evaluated the three methods' specific ability to rank documents that did not match the query, in which case the speriority of CLR over BMR and HCR was apparent

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