Genetic algorithms, association rules mining, temporal quantitative data
Association rule mining has shown great potential to extract knowledge from multidimensional data sets. However, existing methods in the literature are not effectively applicable to quantitative temporal data. This article extends the concepts of association rule mining from the literature. Based on the extended concepts is presented a method to mine rules from multidimensional temporal quantitative data sets using genetic algorithm, called GTARGA, in reference to Quantitative Temporal Association Rule Mining by Genetic Algorithm. Experiments with QTARGA in four real data sets show that it allows to mine several high-confidence rules in a single execution of the method.
Silva, Sergio Francisco; Batista, Marcos Aurélio; and Traina, Agma Juci Machado, "Quantitative temporal association rule mining by genetic algorithm" (2015). Proceedings of the XI Brazilian Symposium on Information Systems (SBSI 2015). 74.