Authors: Guillaume Raschia, Noureddine Mouaddib
Tags: 1998, conceptual modeling
In this paper, we propose a fuzzy attribute-oriented induction method for knowledge discovery in relational databases. This method is adapted from the DBLearn system by representing background knowledge with fuzzy thesauri and fuzzy labels. These models allow to take into account inherent imprecision and uncertainty of the domain representation. We also show the power of fuzzy thesauri and linguistic variables to describe gradations in the generalization process and to handle exceptions.Read the full paper here: https://link.springer.com/chapter/10.1007/978-3-540-49121-7_1
