Abstract
In this study, a fuzzy query tool (SQLf) for non-fuzzy database management systems was developed. In addition, samples of fuzzy queries were made by using real data with the tool developed in this study. Performance of SQLf was tested with the data about the Marmara University students’ food grant. The food grant data were collected in MySQL database by using a form which had been filled on the web. The students filled a form on the web to describe their social and economical conditions for the food grant request. This form consists of questions which have fuzzy and crisp answers. The main purpose of this fuzzy query is to determine the students who deserve the grant. The SQLf easily found the eligible students for the grant through predefined fuzzy values. The fuzzy query tool (SQLf) could be used easily with other database system like ORACLE and SQL server.
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References
Mutlu, T.: A Fuzzy Query Tool For Non-Fuzzy Databases, Master Thesis, Istanbul Technical University Information Sciences Institute, Istanbul (1996)
Bahadır, A.: Flexible Querying in Standard Database Systems With Fuzzy Set Approach, Master Thesis, Istanbul Technical University Information Sciences Institute, Istanbul (1999)
Andersen, T., Christiansen, H., Larsen, H.L.: Flexible Query Answering System, pp. 45–61, 187-209, 247-277. Kluwer Academic Publishers, Boston (1997)
Zadeh, L.A., Kacprzyk, J.: Fuzzy Logic for the Management of Uncertainty, pp. 645–672. Wiley, New York (1992)
Kacprzyk, J., Ziolkowski, A.: Database Queries with Fuzzy Linguistic Quantifiers. IEEE Transactions on Systems, Man and Cybernetics SMC-16(3), 474–478 (1986)
Takahashi, Y.: A Fuzzy Query Language for Relational Databases. IEE Transactions on Systems, Man and Cybernetics 21(6), 1576–1579 (1991)
Rasmussen, D., Yager, R.R.: SummarySQL–A Fuzzy Tool For Data Mining. Intelligent Data Analysis 1(1-4), 49–58 (1997)
Rasmani, K.A., Shen, Q.: A Data-Driven Fuzzy Rule-Based Approach for Student Academic Performance Evaluation. Applied Intelligence 23(3), 305–319 (2006)
Zadeh, L.A.: Knowledge Representation in Fuzzy Logic. IEEE Transactions on Knowledge and Data Engineering 1(1), 89–100 (1989)
Klir, G.J., Yuan, B.: Fuzzy Sets and Fuzzy Logic Theory and Applications, pp. 379–388. Prentice Hall, New Jersey (1995)
Tanaka, K.: An Introduction to Fuzzy Logic for Practical Applications, pp. 68–75. Springer, New Jersey (1996)
Ross, J.T.: Fuzzy Logic with Engineering Applications, pp. 52–75. McGraw Hill Inc, New York (2004)
Kosko, B.: Fuzzy Engineering, pp. 18–24. Prentice Hall, New Jersey (1997)
Zongmin, M.: Fuzzy Database Modeling of Imprecise and Uncertain Engineering Information, pp. 137–155. Springer, New York (2006)
Zimmermann, H.J.: Fuzzy Sets, Decision Making, and Expert Systems, pp. 125–134. Kluwer Academic Publishers, Boston (1987)
Terano, T., Asai, K., Sugeno, M.: Fuzzy Systems Theory and Its Applications. Academic Press, San Diego (1992)
Şen, O.N.: Oracle SQL, SQL*PLUS, PL/SQL and Database Management, Beta Impression Publication Distributor, Istanbul, pp. 85–90 (2000)
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Şimşek, İ., Topuz, V. (2010). Data Processing on Database Management Systems with Fuzzy Query. In: Graña Romay, M., Corchado, E., Garcia Sebastian, M.T. (eds) Hybrid Artificial Intelligence Systems. HAIS 2010. Lecture Notes in Computer Science(), vol 6076. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13769-3_21
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DOI: https://doi.org/10.1007/978-3-642-13769-3_21
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