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Enriching Vague Queries by Type-2 Fuzzy Orderings

Saad M. Darwish1, Tamer F. Mabrouk2, and Yasser F. Mokhtar1
1.Institute of Graduate Studies and Research, Alexandria University, Alexandria, Egypt
2.Alexandria Higher Institute of Engineering & Technology, Alexandria, Egypt
Abstract—Structural Query Language (SQL) is very restrictive and very dominant tool that handles data that is crisp and precise in nature; but it is unable to fulfill the needs for data which is uncertain, imprecise, and vague in nature. The human queries are rarely crisp, which need unusual requirements to deal with it based on world knowledge. These requirements are called Fuzzy Queries (FQ) that realizes some degrees of truth. Mixing the concepts of fuzzy set theory and SQL, FSQL is able to process imprecise and ambiguous data and also able to increase the facility of data retrieval based on linguistic terms. This paper describes a flexible query interface based on type-2 fuzzy logic. Hence, queries in natural language with pre-defined syntactical structures are executed, and the system uses a type-2 fuzzy process to provide answers. Type-2 fuzzy logic (T2FL) system offers the capability of handling a higher level of uncertainty than regular fuzzy logic, which is heavily used in the previous works. T2FL can be used when the situations are too uncertain to decide the exact membership functions. FSQL seems to be a practically feasible and efficient approach to contract with queries for crisp data that include a certain tolerance for imprecision compared to its SQL counterpart. Many experiments have been made on real database that show the effectiveness of the proposed model compared to the existing type-1 fuzzy systems and also show the high accuracy in the results.

Index Terms—SQL, interval type-2 fuzzy logic, fuzzy linguistic values, fuzzy query, fuzzy database

Cite: Saad M. Darwish, Tamer F. Mabrouk, and Yasser F. Mokhtar, "Enriching Vague Queries by Type-2 Fuzzy Orderings," Lecture Notes on Information Theory, Vol. 2, No. 2, pp. 177-185, June 2014. doi: 10.12720/lnit.2.2.177-185
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