International Journal of Computer Science Issues

More than a traditional journal...

Today, mining association rule is one of the important data mining algorithms which enables managers to make correct decisions based on the knowledge obtained from the detected patterns by databases. Traditional algorithms of discovering association rules such as Apriori and FP-growth may extract millions of rules from databases, many of which are useless, and this issue causes managers to face difficulty to make correct decision. One of the main challenges of rule discovery is presenting a method which can extract useful and approach optimal rules. In this paper, attempts were made to present a new method for useful and optimal mining of association rules in database using binary genetic optimization algorithm. The presented method was implemented by MATLAB R2010b programming language and SQL SERVER 2008 database. obtained results indicated that the presented algorithm had a high capability in mining optimal association rules and one of the forte of this method comping with the previous ones was its ability to discover rare rules in large databases.