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A Possibility-Theoretic View of Formal Concept Analysis

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Języki publikacji
EN
Abstrakty
EN
The paper starts from the standard relational view linking objects and properties in formal concept analysis, here augmented with four modal-style operators (known as sufficiency, dual sufficiency, necessity and possibility operators). Formal concept analysis is mainly based on the first operator, while the others come from qualitative data analysis and can be also related to rough set theory. A possibility-theoretic reading of formal concept analysis with these four operators is proposed. First, it is shown that four and only four operators are indeed needed in order to describe the nine situations that can occur when comparing a statement (or its negation) with a state of information. The parallel between possibility theory and formal concept analysis suggests the introduction of new notions such as normalization and conditioning in the latter framework, also leading to point out some meaningful properties. Moreover, the graded setting of possibility theory allows us to suggest the extension of formal concept analysis to situations with incomplete or uncertain information.
Słowa kluczowe
Wydawca
Rocznik
Strony
195--213
Opis fizyczny
bibliogr. 25 poz., tab.
Twórcy
autor
  • Université Paul Sabatier, Institut de recherche en informatique de Toulouse 31062 Toulouse Cedex 9, France, dubois@irit.fr
Bibliografia
  • [1] Barbut, M., Montjardet, B.: Ordre et Classification: Alg`ebre et Combinatoire, Hachette, 1970.
  • [2] Belohlavek, R.: Fuzzy Relational Systems: Foundations and Principles, vol. 20, Kluwer Academic/Plenum Press, New York, 2002.
  • [3] Benferhat, S., Dubois, D., Prade, H.: Representing default rules in possibilistic logic, Proc. of the 3rd Conf. on Knowledge Representation, 1992.
  • [4] Birkhoff, G.: Lattice Theory, American Mathematical Society Colloquium Publications vol. XXV, 1940.
  • [5] Burusco, A., Fuentes-Gonzlez, R.: Construction of the L-fuzzy concept lattice, Fuzzy Sets and Systems, 97(1), July 1998, 109-114.
  • [6] Dubois, D., Fariñas Del Cerro, L., Herzig, A., Prade, H.: A roadmap of qualitative independence , in: Fuzzy Sets, Logics and Reasoning about Knowledge (D. Dubois, H. Prade, E. Klement, Eds.), vol. 15 of Applied Logic series, Kluwer Academic Publishers, Dordrecht, Pays-Bas, 1999, 325-350.
  • [7] Dubois, D., Prade, H.: Possibility Theory: An Approach to Computerized Processing of Uncertainty, Plenum Press, New York, 1988, With the collaboration of H. Farreny, R. Martin-Clouaire, C. Testemale.
  • [8] Dubois, D., Prade, H.: Rough fuzzy sets and fuzzy rough sets, Int. Journal of General Systems, 17(2-3), 1990, 191-209.
  • [9] Dubois, D., Prade, H.: Possiblity theory as a basis for preference propagation in automated reasonning, Proc. of the 1st IEEE Inter. Conf. on Fuzzy Systems (FUZZ-IEEE'92), San Diego, CA, March 1992.
  • [10] Dubois, D., Prade, H.: Possibility theory:qualitative and quantitative aspects, in: Quantified Representation of Uncertainty and Imprecision, vol. 1 of Handbook of Defeasible Reasoning and Uncertainty Management Systems, Kluwer Academic Publishers, The Netherlands, 1998, 169-226.
  • [11] Düntsch, I., Gediga, G.: Approximation operators in qualitative data analysis, in: Theory and application of relational structures as knowledge instruments, Springer, Heidelberg, 2003, 216-233.
  • [12] Düntsch, I., Orlowska, E.: Mixing modal and sufficiency operators, Bulletin of the Section of Logic, Polish Academy of Sciences, 28(2), 1999, 99-106.
  • [13] Düntsch, I., Orlowska, E.: Boolean algebras arising from information systems, Annals of Pure and Applied Logic, 127(Issues 1-3), June 2004, 77-98.
  • [14] Ganter, B.: Two basic algorithms in concept analysis, Technical Report Preprint 831, Technische Hochschule Darmstadt, 1984, 28 p.
  • [15] Ganter, B., Wille, R.: Formal Concept Analysis, Mathematical Foundations, Springer-Verlag, 1999.
  • [16] Gediga, G., Düntsch, I.: Modal-style operators in qualitative data analysis, Proceedings of the 2002 IEEE International Conference on Data Mining, December 9 - 12 2002.
  • [17] McCarthy, J., Hayes, P.: Some philosophical problems from the standpoint of artificial intelligence, in: Machine Intelligence, vol. 4, 1969, 463-502.
  • [18] Nahmias, S.: Fuzzy variables, Fuzzy Sets and Systems, 1(2), 1978, 97-110.
  • [19] Ore, O.: Galois Connexions, Transactions of the American Mathematical Society, 55, 1944, 493-513.
  • [20] Pawlak, Z.: Rough sets, Internat. J. Computer and Information Sciences, 11, 1982, 341-356.
  • [21] Pawlak, Z.: Rough Sets. Theoretical Aspects of. Reasoning about Data, Kluwer Acad. Publ., Dordrecht, 1991.
  • [22] Wille, R.: Restructuring lattice theory: an approach based on hierarchies of concepts, in: Ordered Sets (I. Rival, Ed.), D. Reidel, Dordrecht-Boston, 1982, 445-470.
  • [23] Yao, Y.: A comparative study of formal concept analysis and rough set theory in data analysis, Rough Sets and Current Trends in Computing, 4th International Conference, RSCTC 2004, Uppsala, Sweden, June 1-5 2004.
  • [24] Yao, Y.: Concept lattices in Rough set theory, Proc. of Fuzzy Sets in the Heart of Canadian Rockies conference (NAFIPS-04), June 27-30 2004.
  • [25] Zadeh, L.: Fuzzy sets as a basis for a theory of possibility, Fuzzy Sets and Systems, 1, 1978, 3-28.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BUS5-0009-0010
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