A review on support threshold free frequent itemsets mining approaches

Abstract

Frequent Itemsets (FIs) mining has gained prolific research interest of the data mining community know a days. It is considered a pivotal step for association rule mining. The frequent itemsets mining is NP-complete problem therefore; concerted efforts are made so far to reduce the complexity of this task. The Apriori approach is regarded as the first technique to solve the frequent itemsets mining dilemma. It has highlighted several issues in frequent itemsets mining problem. The conventional frequent itemsets mining methods are dependent on user support threshold. This is considered a vital parameter for frequent itemsets mining. The support threshold parameter has caused unavoidable complexities in frequent itemsets mining problem. Therefore, in this paper we intend to review all the support threshold free frequent itemsets mining methods. At the end a table will present the strength and weakness of the current support threshold free frequent itemsets mining approaches.