Frequent Itemsets Mining with Chemical Reaction Optimization Metaheuristic

Frequent Itemsets mining is a key concept in Association Rule Mining task, it aims to discover the frequent itemsets in a transactional dataset.Nowadays large amounts of data needs to be analysed, thus the use of traditional approaches for mining frequent itemsets suffer from computational time and memory requirement, beside the difficulty for the user to provide an appropriate minimum support value. For these reasons, we propose to tackle the problem of mining frequent itemsets by mean of Chemical Reaction Optimization metaheuristic without the need to specify minsup threshold . The results show that the proposed approach gives good results and it can be used as alternative to mine frequent itemsets.