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Handling of Fuzzy Queries using Relational DBMS

by Nishant Agrawal, Anubhav Manan, Akash Aggrawal, Rashmi Sharma
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 68 - Number 22
Year of Publication: 2013
Authors: Nishant Agrawal, Anubhav Manan, Akash Aggrawal, Rashmi Sharma
10.5120/11714-7365

Nishant Agrawal, Anubhav Manan, Akash Aggrawal, Rashmi Sharma . Handling of Fuzzy Queries using Relational DBMS. International Journal of Computer Applications. 68, 22 ( April 2013), 34-40. DOI=10.5120/11714-7365

@article{ 10.5120/11714-7365,
author = { Nishant Agrawal, Anubhav Manan, Akash Aggrawal, Rashmi Sharma },
title = { Handling of Fuzzy Queries using Relational DBMS },
journal = { International Journal of Computer Applications },
issue_date = { April 2013 },
volume = { 68 },
number = { 22 },
month = { April },
year = { 2013 },
issn = { 0975-8887 },
pages = { 34-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume68/number22/11714-7365/ },
doi = { 10.5120/11714-7365 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:28:38.603622+05:30
%A Nishant Agrawal
%A Anubhav Manan
%A Akash Aggrawal
%A Rashmi Sharma
%T Handling of Fuzzy Queries using Relational DBMS
%J International Journal of Computer Applications
%@ 0975-8887
%V 68
%N 22
%P 34-40
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Handling crisp and precise data in SQL is an easy process but classical data models often suffer from their incapability of representing and manipulating imprecise and uncertain information which is found in many real world applications. Since the early 1980's, Zadeh'sfuzzy logic has been used to improve and modify various data models. This introduction of fuzzy logic in databases enhances the capability of classical models so that uncertain and imprecise information could easily be represented and manipulated. This paper proposes an algorithm with the help of which crisp values are converted into fuzzy values by calculating their membership value at the database level. The paper then uses a GUI through which the result of fuzzy queries can be obtained from the database. With the help of proposed algorithm, the calculated membership value will be stored in the database for differentpredefined categories (e. g. -child, young, middle age and old in case of ages). These membership values helps in fetching the result of fuzzy queries from the database with the help of developed GUI (the database used here is oracle 10g but other databases can also be used). The fuzzy queries have a wider retrieved space and can be used to identify the characteristic of an individual (marks in this case).

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Index Terms

Computer Science
Information Sciences

Keywords

Handling Fuzzy

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