Mining dynamical frequent itemsets based on ant colony algorithm
Chen ShengBing, Xiaofeng Wang, Wang XiaoFang · 2011
Mining frequent itemsets is a core problem in many data mining tasks, most existing works on mining frequent itemsets can only capture the long-term and static frequency itemsets, they do not suit the task whose frequent itemsets often change. Using the theory of ant colony algorithm, we proposed a new method for mining dynamical frequent itemset(called AC-MFI). The method considers the item of transaction as a node in the path, takes the itemset as a path, and takes each transaction as a foraging behavior. According to the pheromone updating policy of ant colony algorithm, AC-MFI mines dynamical frequent itemsets from transaction data stream. Experiment results show that the method is valid and practicable.