Integration of data selection and classification by fuzzy logic

  • Authors:
  • Miroslav Hudec;Mirko Vujošević

  • Affiliations:
  • INFOSTAT - Institute of Informatics and Statistics, Dúbravská cesta 3, 84524 Bratislava, Slovakia;Faculty of Organizational Sciences, University of Belgrade, Jove Ilića 154, 11000 Beograd, Serbia

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2012

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Abstract

A concept of integration of fuzzy data selection and classification by fuzzy Generalized Logical Condition (GLC) is presented in this paper. The GLC that extends SQL queries with fuzzy logic was developed for the purpose of fuzzy data selection. In order to classify data by generating fuzzy queries from fuzzy rules, the extension of the GLC was created. The proposed methodology leads to the integration of data selection and data classification into one entity, while the access to relational databases remains unchanged. The obtained approach was presented on data from the municipal and urban statistical database. Data selection and classification problems can often be described more naturally in terms of natural language rather than by crisp numbers.