Comparative Optimization of Efficient Association Rule Mining through PSO and GA

Data mining is a task to find useful information from databases. One of the important topics in data mining is to find hidden patterns from the existing databases. In data mining Association rule mining is the task of discovering association that occur frequently in a given data set. Association rules have been extensively studied in the literature for their usefulness. In this research paper, the emphasis is to generate Positive and negative association rules using Particle Swarm Optimization and Genetic algorithm. The main aim of this research paper is to compare result generated from both algorithms. Here we tried to find out best one optimization algorithm for getting efficient association rules either positive or negative.