International Science Index


10008697

Similarity Based Membership of Elements to Uncertain Concept in Information System

Abstract:

The process of determining the degree of membership for an element to an uncertain concept has been found in many ways, using equivalence and symmetry relations in information systems. In the case of similarity, these methods did not take into account the degree of symmetry between elements. In this paper, we use a new definition for finding the membership based on the degree of symmetry. We provide an example to clarify the suggested methods and compare it with previous methods. This method opens the door to more accurate decisions in information systems.

References:
[1] A. Elshenawy, M. Kamel Elsayed and E. Esodany, Weighted membership based on matrix relation, Mathematical Methods in the Applied Sciences, 2017.
[2] A. Oellicel, E. Leandor, G. Lambert, L. Eduardo and P. Rodrigues, "Intelligent Data Mining for Turbo-Generator Predictive Maintenance: An Approach in Real-world".
[3] E. Lashin, AM. Kozae, A. A. Abo Khadra, and T. Medhat, Rough set theory for topological spaces. Int. J. Approx. Resoning, 40, 35-43, 2005.
[4] K. Atanassov, Intuitionistic fuzzy sets, Fuzzy Sets and Systems, 20, 87-96, 1986.
[5] L. A. Zadeh, Fuzzy Sets, Inform. And Control, 8, 338-353, 1965.
[6] R. Intan and M. Mukaidono, Generalization of rough membership function based on a-converings of the universe, N. R. Pal and M. Sugeno (Eds.), 129-136, 2002.
[7] R. Slowinski, D. Vanderpooten, A generalized definition of rough approximations based similarity, IEEE Trans. Data Knowledge Eng, 2, 331-336, 2002.
[8] T. Herawan and W. Meseri, Rough set membership function-based for clustering web transactions, International Journal of Multimedia and Ubiquitous engineering, 8, 105-118, 2013.
[9] Z. Pawlak, Rough Sets, International Journal of Computer and Information Science, 11 (5), 341-356, 1982.
[10] Z. Pawlak, Rough sets, theoretical aspects of reasoning about data: Kluwer Academic Publishers, 248, 1992.
[11] Z. Pawlak and A. Skowran, Rough membership functions: A tool for reasoning with uncertainty, algebraic method in logic and in computer science, 28, 135-149, 1993.
[12] Z. Huang, "A fast Clustering Algorithm to Cluster Very Large Categorical Data Sets in Data Mining".