A System for Mining Generalized Association Rules with Ontology Using Genetic Network Programming

Abstract

In this paper, we propose a genetic network programming based system to mine equalized association rules in multi concept layers of ontology. There are three modules in this system: database, equalizer and GNP miner. We first introduce ontology to facilitate building the multi concept layers in Database module and propose dynamic threshold approach (DTA) to equalize the different layers in Equalizer. We make use of an evolutionary computation method genetic network programming (GNP) to mine the rules and develop a new genetic operator to speed up searching the rule space.