In this paper genetic based method proposed for mining association rule, the benefit of this method it mining association rule in one step and it does not require the user-specified threshold of minimum support and minimum confidence deciding suitable threshold values of support and confidence is critical to the quality of association rule technology. Specific mechanisms for crossover operators have been designed to extract interesting rules from a transaction database.
The method proposed in this paper is successfully applied to real-world database. The results demonstrate that the proposed algorithm is a practical method for mining association rules.