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

• Authors: Krzysztof Pancerz , Arkadiusz Lewicki

Title variants

PL

Ekstrakcja reguł decyzyjnych z danych lingwistycznych opisujących zjawiska ekonomiczne. Podejście oparte na systemach decyzyjnych nad grafami ontologicznymi oraz optymalizacji rojem cząstek

• Languages of publication: EN

Abstracts

EN

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.

PL

Celem artykułu jest przedstawienie heurystycznej metody ekstrakcji najbardziej ogólnych reguł decyzyjnych z danych lingwistycznych, opisujących zjawiska ekonomiczne, zawartych w systemach decyzyjnych nad grafami ontologicznymi. Systemy decyzyjne tego typu zaproponowane zostały w celu poradzenia sobie z lingwistycznymi wartościami atrybutów opisującymi rozważane obiekty, które są pojęciami umieszczonymi w przestrzeniach semantycznych reprezentowanych przez grafy ontologiczne. Grafy ontologiczne dostarczają nam pewną dodatkową wiedzę (tzw. wiedzę bazową) o relacjach semantycznych pomiędzy pojęciami, która może być pomocna w procesach klasyfikacji. Jako heurystykę zaproponowano optymalizację rojem cząstek (Particle Swarm Optimization ) uważaną za metodę odnoszącą sukces w wielu zastosowaniach.

Keywords

EN

decision rules; decision systems; ontological graphs; particle swarm optimization

• Publisher: Wyższa Szkoła Zarządzania i Administracji w Zamościu
• Journal: Barometr Regionalny. Analizy i prognozy
• Year: 2014
• Issue: 1(35)
• Pages: 133-140

Contributors

author

Krzysztof Pancerz

• University of Management and Administration in Zamość
• University of Information Technology and Management in Rzeszów

author

Arkadiusz Lewicki

• University of Information Technology and Management in Rzeszów

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