A COMPARATIVE ANALYSIS OF UNCERTAIN QUERY PROCESSING USING FUZZY SETS AND VAGUE SETS
Keywords:
Fuzzy set, Vague set, Similarity measure, SQLAbstract
The most important aspect in the utilization of a database system is its ability of processing information and queries correctly. The objective of the present paper is to analyze and compare the performance of fuzzy and vague database models with respect to processing of uncertain queries. An algorithm has been designed for that purpose and has been successfully applied to queries related to real life examples. The study reveals that vague sets produce more accurate decisions in comparison to fuzzy sets and thus a DBMS that uses vague theoretic concept may become a more powerful software product than those currently available.
References
I. L. A. Zadeh, “Fuzzy Sets”, Information and Control, Vol. 8, No. 3, pp. 338-353, 1965.
II. R. Intan and M. Mukaidono, “Fuzzy functional dependency and its application to approximate data querying”, in Proceedings of international Database Engineering and Applications Symposium, pp. 47-54, 2000.
III. Y. Takahashi, “Fuzzy database query languages and their relational completeness theorem”, IEEE Transactions on Knowledge and Data Engineering, Vol. 5, pp. 122-125, 1993.
IV. P. Bosc and O. Pivert, “SQLF: a relational database language for fuzzy querying”, IEEE Transaction on Fuzzy Systems, Vol. 3, No. 1, pp. 1-17, 1995.
V. H. Nakajima et al., “Fuzzy Database Language and Library- Fuzzy Extension to SQL”, Second IEEE International Conference on Fuzzy Systems, Vol. 1, pp. 477-482, 1993.
VI. Moreau A., Pivert O. and Smits G., “Fuzzy Query by example.”, 33rd ACM / SIGAPP Symposium On Applied Computing (SAC-2018), France, 2018.
VII. Srivastava A., et al., “Fuzzy Query: An Impression in Query processing”, Proceedings of IEEE Sponsored International Conference on Advancement in Computer Engineering and Information Technology (ACEIT 2016), 2016.
VIII. W. L. Gau and D. J. Buehrer, “Vague Sets”, IEEE Trans. Syst. Man, Cybernetics, Vol. 23, No. 2, pp.610-614, 1993.
IX. A. Lu and W. Ng, “Vague Sets or Intuitionist Fuzzy Sets for Handling Vague data: Which One Is Better?”, Lecture Notes in Computer Science, Vol. 3716, pp. 401-416, 2005.
X. F. Zhao and Z. M. Ma, “Vague Query Based on Vague Relational Model”, AISC 61, pp. 229-238, Springer-Verlag Berlin Heidelberg, 2009.
XI. A. K. Dutta, S. Idwan and R. Biswas, “A Study of Vague Search to Answer Imprecise Query”, International Journal of Computational Cognition, Vol. 7, No. 4, pp. 63-69, 2009.
XII. J. Mishra, “An Extension of Fuzzy Relational Database Model into Vague Relational Database Model”, Ph.D. Thesis, West Bengal University of Technology, 2014.
XIII. J. Mishra and S. Ghosh, “Uncertain Query Processing using Vague Set or Fuzzy Set : Which One Is Better?”, International Journal of Computers Communications & Control, Vol. 9, No. 6, pp. 730-740, 2014.
XIV. Raju and A. K. Majumdar, “Fuzzy functional dependencies and lossless join decomposition of fuzzy relational database system”, ACM Transactions on Database Systems, Vol. 13, No. 2, pp. 129-166, 1988.
XV. Z. M. Ma and X. Meng, “A Knowledge-Based Approach for Answering Fuzzy Queries over Relational Databases”, LNAI 5178, pp. 623-630, Springer-Verlag Berlin Heidelberg, 2008.
XVI. S. M. Chen, “Similarity Measure between Vague Sets and between Elements”, IEEE Trans. Systems. Man and Cybernetics, Vol. 27, No. 1, pp. 153-158, 1997.
XVII. D. H. Hong and C. Kim, “A Note on Similarity Measures between Vague Sets and between Elements”, Information Sciences, Vol. 115, pp. 83-96, 1999.
XVIII. F. Li and Z. Xu, “Measures of Similarity between Vague Sets”, Journal of Software, Vol. 12, No. 6, pp. 922-927, 2001.
XIX. A. Lu and W. Ng, “Managing Merged Data by Vague Functional Dependencies” Springer-Verlag Berlin Heidelberg LNCS 3288, pp. 259-272, 2004.
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