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Priss, U.: Faceted knowledge representation (1999)
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- Abstract
- Faceted Knowledge Representation provides a formalism for implementing knowledge systems. The basic notions of faceted knowledge representation are "unit", "relation", "facet" and "interpretation". Units are atomic elements and can be abstract elements or refer to external objects in an application. Relations are sequences or matrices of 0 and 1's (binary matrices). Facets are relational structures that combine units and relations. Each facet represents an aspect or viewpoint of a knowledge system. Interpretations are mappings that can be used to translate between different representations. This paper introduces the basic notions of faceted knowledge representation. The formalism is applied here to an abstract modeling of a faceted thesaurus as used in information retrieval.
- Date
- 22. 1.2016 17:30:31
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Wille, R.: Concept lattices and conceptual knowledge systems (1992)
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Scheich, P.; Skorsky, M.; Vogt, F.; Wachter, C.; Wille, R.: Conceptual data systems (1992)
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Prediger, S.: Kontextuelle Urteilslogik mit Begriffsgraphen : Ein Beitrag zur Restrukturierung der mathematischen Logik (1998)
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- Date
- 26. 2.2008 15:58:22
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Scheich, P.; Skorsky, M.; Vogt, F.; Wachter, C.; Wille, R.: Conceptual data systems (1993)
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-
Rusch, A.; Wille, R.: Knowledge spaces and formal concept analysis (1996)
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- Source
- Data analysis and information systems, statistical and conceptual approaches: Proceedings of the 19th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Basel, March 8-10, 1995. Ed.: H.-H. Bock u. W. Polasek
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Vogt, F.; Wille, R.: TOSCANA - a graphical tool for analyzing and exploring data (1995)
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- Source
- Knowledge organization. 22(1995) no.2, S.78-81
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Reinartz, T.P.; Zickwolff, M.: ¬Two conceptual approaches to acquire human expert knowledge in a complex real world domain (1996)
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- Source
- Data analysis and information systems, statistical and conceptual approaches: Proceedings of the 19th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Basel, March 8-10, 1995. Ed.: H.-H. Bock u. W. Polasek
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Groh, B.; Strahringer, S.; Wille, R.: TOSCANA-systems based on thesauri (1998)
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-
Luksch, P.; Wille, R.: ¬A mathematical model for conceptual knowledge systems (1991)
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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
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Neuss, C.; Kent, R.E.: Conceptual analysis of resource meta-information (1995)
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- Source
- Computer networks and ISDN systems. 27(1995) no.6, S.973-984
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Ganter, B.; Wille, R.: Formal concept analysis : mathematical foundations (1998)
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- Abstract
- This is the first textbook on formal concept analysis. It gives a systematic presentation of the mathematical foundations and their relation to applications in computer science, especially data analysis and knowledge processing. Above all, it presents graphical methods for representing conceptual systems that have proved themselves in communicating knowledge. Theory and graphical representation are thus closely coupled together. The mathematical foundations are treated thouroughly and illuminated by means of numerous examples. Since computers are being used ever more widely for knowledge processing, formal methods for conceptual analysis are gaining in importance. This book makes the basic theory for such methods accessible in a compact form
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Priss, U.; Jacob, E.: Utilizing faceted structures for information systems design (1999)
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