|International Journal of Applied Information Systems
|Foundation of Computer Science (FCS), NY, USA
|Volume 5 - Number 3
|Year of Publication: 2013
|Authors: Basheer Mohamad Al-Maqaleh
Basheer Mohamad Al-Maqaleh . Discovering Interesting Association Rules: A Multi-objective Genetic Algorithm Approach. International Journal of Applied Information Systems. 5, 3 ( February 2013), 47-52. DOI=10.5120/ijais12-450873
Association rule mining is considered as one of the important tasks of data mining intended towards decision making process. It has been mainly developed to identify interesting associations and/or correlation relationships between frequent itemsets in datasets. A multi-objective genetic algorithm approach is proposed in this paper for the discovery of interesting association rules with multiple criteria i. e. support, confidence and simplicity (comprehensibility). With Genetic Algorithm (GA), a global search can be achieved and system automation is developed, because the proposed algorithm could identify interesting association rules from a dataset without having the user-specified thresholds of minimum support and minimum confidence. The experimental results on various types of datasets show the usefulness and effectiveness of the proposed algorithm.