A new approach for fuzzy classification in relational databases

Authors:
Ricardo Hideyuki Tajiri;Eduardo Zanoni Marques;Bruno Bogaz Zarpelão;Leonardo de Souza Mendes
Affiliations:
Department of Communication, School of Electrical and Computer Engineering, University of Campinas, SP, Brazil;Department of Communication, School of Electrical and Computer Engineering, University of Campinas, SP, Brazil;Department of Communication, School of Electrical and Computer Engineering, University of Campinas, SP, Brazil;Department of Communication, School of Electrical and Computer Engineering, University of Campinas, SP, Brazil
Venue:
DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part II
Year:
2011

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Abstract

This paper presents an easy-to-use and easy-to-implement framework for fuzzy data classification and extraction in relational databases. The main benefits of the framework are: (i) a fuzzy data classification model for relational databases; (ii) flexible membership function configuration; (iii) automatic membership degree computation; (iv) a fuzzy data retrieval mechanism fully supported in SQL queries. In order to validate the proposed framework, a case study is implemented in a social welfare system using RDBMS Oracle 11g and PL/SQL programming language.