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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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Kaytoue, M.; Kuznetsov, S.O.; Assaghir, Z.; Napoli, A.: Embedding tolerance relations in concept lattices : an application in information fusion (2010)
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- Abstract
- Formal Concept Analysis (FCA) is a well founded mathematical framework used for conceptual classication and knowledge management. Given a binary table describing a relation between objects and attributes, FCA consists in building a set of concepts organized by a subsumption relation within a concept lattice. Accordingly, FCA requires to transform complex data, e.g. numbers, intervals, graphs, into binary data leading to loss of information and poor interpretability of object classes. In this paper, we propose a pre-processing method producing binary data from complex data taking advantage of similarity between objects. As a result, the concept lattice is composed of classes being maximal sets of pairwise similar objects. This method is based on FCA and on a formalization of similarity as a tolerance relation (reexive and symmetric). It applies to complex object descriptions and especially here to interval data. Moreover, it can be applied to any kind of structured data for which a similarity can be dened (sequences, graphs, etc.). Finally, an application highlights that the resulting concept lattice plays an important role in information fusion problem, as illustrated with a real-world example in agronomy.
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Ganter, B.; Wille, R.: Formale Begriffsanalyse : Mathematische Grundlagen (1996)
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- Abstract
- This first textbook in the field of formal concept analysis provides a systematic presentation of the mathematical foundations and their relation to applications in informatics, especially data analysis and knowledge processing
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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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Eklund. P.W.: Logic-based networks : concept graphs and conceptual structures (2000)
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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
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Priss, U.: Formal concept analysis in information science (2006)
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- Date
- 13. 7.2008 19:29:59
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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
-
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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Priss, U.: Faceted information representation (2000)
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- Date
- 22. 1.2016 17:47:06
