Extracting Decision Rules from Linguistic Data Describing Economic Phenomena. The Approach Based on Decision Systems over Ontological Graphs and PSO

The aim of the paper is to present a heuristic method for extracting the most general decision rules from linguistic data describing economic phenomena included in simple decision systems over ontological graphs. Such decision systems have been proposed to deal with linguistic attribute values, describing objects of interest, which are concepts placed in semantic spaces expressed by means of ontological graphs. Ontological graphs deliver some additional knowledge (the so-called background knowledge) about semantic relations between concepts which can be useful in classification processes. As heuristics, we propose to use Particle Swarm Optimization (PSO ), which is reported as a successful method in many applications.