Learning preferences in Qualitative Choice Logic and some of its variants: an application for antibiotics recommendations

Qualitative Choice Logic (<i>QCL</i>) is a non-classical logic for representing and reasoning with preferences. It adds to classical propositional logic a new connective called ordered disjunction (×→). x×→y intuitively means: if possible <i>x</i>, but if <i>x</i> is not possible then at least <i>y</i>. Different variants of <i>QCL</i> have been proposed. Among them, we cite Prioritised Qualitative Choice Logic, Conjunctive Choice Logic and Lexicographic Choice Logic. In this paper, we propose a method for learning preferences in the context of <i>QCL</i>. The method is based on an adaptation of association rules based on APRIORI algorithm. The adaptation consists of (1) generating rules that have propositional formulas in their antecedent instead of itemsets and (2) using variations of the support and confidence measures according to the semantics of <i>QCL</i>. We show that <i>QCL</i> is fully adapted for modelling experts reasoning for providing recommendations of antibiotics. Another contribution of the paper concerns a generalisation of the proposed method for learning preferences in the context of <i>QCL</i> variants.