Implementation of fuzzy classification in relational databases using conventional SQL querying |
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| Affiliation: | 1. Departamento de Engenharia de Alimentos, Faculdade de Zootecnia e Engenharia de Alimentos, Universidade de São Paulo, Av. Duque de Caxias – Norte, 225, CEP 13635–900, Pirassununga, SP, Brazil;2. Departamento de Agroindústria, Alimentos e Nutrição, Escola Superior de Agricultura Luiz de Queiroz, Universidade de São Paulo, Piracicaba, SP, Brazil;3. Departamento de Análises Clínicas, Toxicológicas e Bromatológicas, Faculdade de Ciências Farmacêuticas de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP, Brazil;4. Laboratório de Zoonoses Bacterianas, Instituto Oswaldo Cruz, Rio de Janeiro, RJ, Brazil;5. Instituto Federal de Educação, Ciência e Tecnologia do Rio de Janeiro, Rio de Janeiro, RJ, Brazil;1. Université de Strasbourg, ICube UMR 7357, Illkirch-Graffenstaden F-67412, France;2. CNRS, ICube UMR 7357, Illkirch-Graffenstaden F-67412, France;3. ENGEES, ICube UMR 7357, Strasbourg F-67000, France;4. LIRMM, Université de Montpellier, CNRS, Montpellier Cedex 5 F-34392, France |
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| Abstract: | In this paper, a framework for implementing fuzzy classifications in information systems using conventional SQL querying is presented. The fuzzy classification and use of conventional SQL queries provide easy-to-use functionality for data extraction similar to the conventional non-fuzzy classification and SQL querying. The developed framework can be used as data mining tool in large information systems and easily integrated with conventional relational databases. The benefits of using the presented approach include more flexible data analysis and improvement of information presentation at the report generation phase. To confirm the theory, a prototype was developed based on the stored procedures and database extensions of Microsoft SQL Server 2000. |
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