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Reseach Article

Fuzzy to SQL Conversion using Gefred Model with the help of MATLAB

by Poonam
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 104 - Number 17
Year of Publication: 2014
Authors: Poonam
10.5120/18304-9390

Poonam . Fuzzy to SQL Conversion using Gefred Model with the help of MATLAB. International Journal of Computer Applications. 104, 17 ( October 2014), 32-37. DOI=10.5120/18304-9390

@article{ 10.5120/18304-9390,
author = { Poonam },
title = { Fuzzy to SQL Conversion using Gefred Model with the help of MATLAB },
journal = { International Journal of Computer Applications },
issue_date = { October 2014 },
volume = { 104 },
number = { 17 },
month = { October },
year = { 2014 },
issn = { 0975-8887 },
pages = { 32-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume104/number17/18304-9390/ },
doi = { 10.5120/18304-9390 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:36:26.691076+05:30
%A Poonam
%T Fuzzy to SQL Conversion using Gefred Model with the help of MATLAB
%J International Journal of Computer Applications
%@ 0975-8887
%V 104
%N 17
%P 32-37
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

For Many Years, achieving unambiguous knowledge has been turned to a serious challenge for human being. The aim of this paper is to emphasize situation when classical {true, false} logic is not adequate for data selection and data classification. Linguistic expression like: high salary, young etc are very often used in life and in statistics. The goal of this paper is brief study of fuzzy logic and sets and how to make it suitable for database queries and classification tasks. Fuzzy approach is introduced with usual relational database model to handle linguistic queries. The purposed fuzzy approach provides flexibility when users cannot unambiguously set hidden boundaries between data. Our work gives the flexibility to query the database in natural language using FRDB, which permits to have a range of answers in order to offer to the user all intermediate variations, which in turn will enhance the expressiveness of human expression, without any effect on searching time and with reduced cost. In this paper we are using Query Builder tool of MATLAB to show the result of query. Fuzzy query interpreter helps to convert fuzzy query into SQL query without need to learn a new query language. In this paper, we extend the work of medina et al. to implement a new architecture of fuzzy DBMS based on the GEFRED model. This architecture is based on the concept of weak coupling with the DBMS SQL Server.

References
  1. Amel Grissa T. and Mohamed Hassine, “New Architecture of Fuzzy Database Management Systems,” The International Arab Journal of Information Technology, Vol. 6, No. 3, July 2009 213
  2. Ben Hassine A., Grissa A.,Galindo J. and Ounelli H., “ IGI Global: How to achieve Fuzzy Relational Databases Managing Fuzzy Data and Metadata” 2008
  3. “FRDBMS for Fuzzy Querying based on GEFRED Model” IJCA Proceedings on National Workshop-Cum-Conference on (RTMC2011), 2012.
  4. Galindo J., Urrutia A., and Piattini M., Fuzzy Databases: Modeling, Design and Implementation, Idea Group Publishing, Hershey, 2005.
  5. Grissa A., Ben Hassine A., and Ounelli H., “Extended_FSQL_Server: A Server for the Description and the Manipulation of FRDB,” in Proceedings of the 4th International Multi Conference on Computer Science and Information Technology (CSIT), Jordan, pp. 454- 464, 2006.
  6. Jose Galindo, “Handbook of research on fuzzy information processing in databases” IGI Global, 2008.
  7. Medina M., Pons O., and Vila A., “GEFRED: A Generalized Model of Fuzzy Relational Data Bases”, Computer Journal of Information Sciences, vol. 76, no. 1, pp. 87-109, 1994.
  8. Miroslav Hudec, “An Approach to Fuzzy Database Querying, Analysis and Realisation”, UDC 004.4’2, DOI: 10.2298/csis0902127H, 2009.
  9. P Gupta, “FUZZY QUERYING IN TRADITIONAL DATABASE,” International Journal of Artificial Intelligence and Knowledge Discovery, Vol. 1, No.4, 2011.
  10. S.K.Mondal, J.sen, Md.R.Islam and Md.S.Hossian, “Performance comparison of fuzzy queries on fuzzy database and classical database,” International journal of Computer Application Issue 3, Volume1 (February 2013)
  11. Dr. Rahul Rishi and Punkaj Gupta,”Database Design for Storage of Fuzzy Information inTraditional Datbase,”IJCA Journal,2011
  12. Handbook of Research on Fuzzy Information Processing in Databases by José Galindo,Volume 1
Index Terms

Computer Science
Information Sciences

Keywords

Fuzzy SQL membership function query builder tool