Linguistic knowledge base simplification regarding accuracy and interpretability

This work proposes a new method in order to simplify linguistic knowledge bases. The main goal consists of improving simultaneously accuracy and interpretability when it is possible, or at least ensuring a good trade-off between them, as well as consistency of the final knowledge base. It is used with linguistic rules which can be defined by expert, induced by data, or both of them. The simplification process is applied to the well known wine classification problem. The results are encouraging.