[DERBY-6487] I've been working with Derby to make it possible to assist fuzzy based queries. Analysing imprecise data hidden inside crisp data is famous among researchers.Intention of opening a JIRA issue is submitting Paper for Apache community to review.

• Type: Improvement
• Status: Open
• Priority: Major
• Resolution: Unresolved
• Component/s: Miscellaneous, SQL
• Labels: fuzzy imprecise innovation sql
• Assignee: Unassigned
• Reporter: Madushanka Fonseka
• Created: 19/Feb/14 17:50
• Updated: 21/Feb/14 17:02

Description

I have selected fuzzy logy as my model of computing and Derby as my database. So "Select * from employee where salary is high " can be executed. I'll provide more insights in future.

INTRODUCTION : Relational database systems manage only crisp data.Relational models lack flexibility in defining and handling vague data. Due to the limitations in Relational models & SQL intelligent querying cannot be made against relational databases.This research is an effort to enhance & extend relational model to assist fuzzy query in relational models. Fuzzy queries are linguistic expressions and based on SQL.

MOTIVATION
Relational databases are pervasive in modern day computing.
Corperate relational databases contain large amount of data which can be used to provide intelligent solutions.
Relational database systems can be extended for data mining and machine learning operations.

Why Fuzzy Set Theory ?
• In order to study the contextual semantics of vague data Fuzzy Set Theory provides an ideal framework.
• Both Fuzzy Set Theory and Relational Database Theory based on “Sets”. • Hence, joining them together makes a strong framework to study imprecise data.
• Linguistic expressions closed to natural language could be defined using fuzzy logy.