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. © 2011 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Tajiri, R. H., Marques, E. Z., Zarpelão, B. B., & De Souza Mendes, L. (2011). A new approach for fuzzy classification in relational databases. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6861 LNCS, pp. 511–518). Springer Verlag. https://doi.org/10.1007/978-3-642-23091-2_45
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