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We already know that Structured Query Language (SQL) is a very powerful tool. It handles data, which is crisp and precise in nature.but it is unable to satisfy the needs for data which is uncertain, imprecise, inapplicable and vague in nature. The goal of this work is to use Fuzzy techniques i.e linguistic expressions and degrees of truth whose result are presented in this paper. For this purpose we have developed the fuzzy generalized logical condition for the WHERE part of SQL. In this way, fuzzy queries are accessing relational databases in the same way as with SQL. These queries with linguistic hedges are converted into Crisp Query, by deploying an application layer over the Structured Query Language.
Dr. Amit Garg. 1970. \u201cQuerying Capability Enhancement in Database Using Fuzzy Logic\u201d. Unknown Journal GJCST Volume 12 (GJCST Volume 12 Issue 6): .
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Total Score: 112
Country: India
Subject: Uncategorized
Authors: Dr. Amit Garg, Dr. Rahul Rishi (PhD/Dr. count: 2)
View Count (all-time): 142
Total Views (Real + Logic): 20482
Total Downloads (simulated): 11083
Publish Date: 1970 01, Thu
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We already know that Structured Query Language (SQL) is a very powerful tool. It handles data, which is crisp and precise in nature.but it is unable to satisfy the needs for data which is uncertain, imprecise, inapplicable and vague in nature. The goal of this work is to use Fuzzy techniques i.e linguistic expressions and degrees of truth whose result are presented in this paper. For this purpose we have developed the fuzzy generalized logical condition for the WHERE part of SQL. In this way, fuzzy queries are accessing relational databases in the same way as with SQL. These queries with linguistic hedges are converted into Crisp Query, by deploying an application layer over the Structured Query Language.
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