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Fuzzy functional dependencies within the possibilistic databases framework

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The paper deals with fuzzy functional dependencies in relational databases. For data representation a possibility-based approach has been used. It is assumed, that attribute values are represented by means of interval-valued possibility distributions. According to this approach extended definitions of fuzzy functional dependency and fuzzy normal forms have been introduced.
Rocznik
Tom
Strony
75--86
Opis fizyczny
Bibliogr. 27 poz., rys., tab.
Twórcy
  • Politechnika Łódzka, Wydział Fizyki Technicznej, Informatyki i Matematyki Stosowanej
Bibliografia
  • [1] Motro A. Imprecision and Uncertainty in Database Systems. in Studies in Fuzziness: Fuzziness in Database Management Systems, P.Bosc and J. Kacprzyk (eds.), Physica Verlag, 1995
  • [2] Zadeh L. A. Fuzzy sets. Information and Control, 8, 1965, 338-353
  • [3] Galindo J., Urutia A, Piattini M. Fuzzy Databases. Modelling, Design and Implementation. Idea Group Publishing, Londyn 2005
  • [4] Ma Z.M., Zhang W.J., Ma W.Y. Extending object-oriented databases for fuzzy information modeling. Information Systems, 29, 2004, 421-435
  • [5] Yazici A., Georgie R. Fuzzy Database Modelling. Physica Verlag, Heidelberg, 1999
  • [6] Chen G.Q. Fuzzy logic in Data Modeling – semantics, constraints and database design Kluwer, Boston, 1998
  • [7] Ma Z.M., Zhang W.J., Ma W.Y. Chen G.Q. Conceptual Design of Fuzzy Object-Oriented Databases Using Extended Entity-Relationship Model. International Journal of Intelligent Systems, 16, 2001, 697-711
  • [8] Buckles B.P., Petry F.E. A Fuzzy Representation of Data for Relational Databases. Fuzzy Sets and Systems, 7, 1982, 213-226
  • [9] Prade H., Testemale C. Generalizing Database Relational Algebra for the Treatment of Incomplete and Uncertain Information and Vague Queries, Information Science, 34, 1984, 115-143
  • [10] Mańko J., Niewiadomski A. Cardinality and Probability under intuitionistic and interval-valued fuzzy sets. Journal of Applied Computer Science, 14, 2006, 31-41
  • [11] Niewiadomski A. Methods for the linguistic summarization of data: applications of fuzzy sets and their extensions. EXIT, Warszawa, 2008
  • [12] Sambuc R. Founctions F-floues. Application á l’aide au diagnostic en pathologie thyroidienne. PhD thesis, University de Marseillé, France, 1975
  • [13] Karnik N.N., Mendel J.M. An Introduction to Type-2 Fuzzy Logic Systems. University of Southern California, Los Angeles, 1998
  • [14] Shenoi S., Melton A., Fan L.T. Functional dependencies and normal forms in the fuzzy relational database model. Information Sciences, 60, 1992, 1-28
  • [15] Sozat M., Yazici A. A complete axiomatization for fuzzy functional and multivalued dependencies in fuzzy database relations. Fuzzy Sets and Systems, 117, 2001, 161-181
  • [16] Raju, K.V.S.V.N., Majumdar, A.K. Fuzzy Functional Dependencies and Lossless Join Decomposition of Fuzzy Relational Database Systems. ACM Trans. On Database Systems 13, 1988, 120-166
  • [17] Cubero, J.C., Vila, M. A. A new definitions of fuzzy functional dependency in fuzzy relational databases. International Journal for Intelligent Systems, 9, 1994, 441-448
  • [18] Kumar D., Hmoudab M., Biswas R. A Method of Intuitionistic Fuzzy Functional Dependencies in Relational Databases. European Journal of Scientific Research, Vol. 29, No. 3, 2009, 415-425
  • [19] Arora M., Biswas R. Rank Neutrosophic Armstrong Axioms and Functional Dependencies. International Journal of Computer Science and Communication, Vol. 1, No. 2, 2010, 447-450
  • [20] Bahar O., Yazici A. Normalization and Lossless Join Decomposition of Similaritybased Fuzzy Relational Databases. International Journal of Intelligent Systems, 19, 2004, 885-917
  • [21] de Tre G., de Caluwe R. Level-2 fuzzy sets and their usefulness in object-oriented database modeling. Fuzzy Sets and Systems, 140, 2003, 29-49
  • [22] Atanasow K.T., Intuitionistic fuzzy sets. Theory and Applications. Springer Verlag, 1999
  • [23] Gau W.L., Buehrer D.J. Vague sets. IEEE Transactions Systems Man Cybernetics. 23, 1993, 610-614
  • [24] Sengupta AQ., Pal T. K., Chakraborty D. Interpretation of inequality constraints involving interval coefficients and a solution to interval linear programming. Fuzzy Sets and Systems, 119, 2001, 129-138
  • [25] Cornelis C., Deschrijver G. The compositional rule of inference in an intuitionistic fuzzy logic setting. in Striegnitz K. (Ed), Proc. Sixth ESSLLI Students Session, 2001
  • [26] Alcade C., Burusco A., Fuentes-Gonzales R. A constructive method for the definition of interval-valued fuzzy implication operators. Fuzzy Sets and Systems, 153, 2005, 211-227
  • [27] Myszkorowski K. Fuzzy Functional Dependencies in Multiargument Relationships. In Rutkowski L., Scherer R., Tadeusiewicz R., Zadeh L.A., Żurada J.M. (Eds.), ICAISC (2010), LNCS 6113, 152-159, Springer, Heidelberg, 2011
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPS3-0022-0082
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