A Frequent Pattern Mining Algorithm Based on Fp-tree Structure Andapriori Algorithm

Association rule mining is used to find association relationships among large data sets. Mining frequent patterns is an importantaspect in association rule mining. In this paper, an algorithm named Apriori-Growth based on Apriori algorithm and the FP-tree structure is presented to mine frequent patterns. The advantage of the Apriori-Growth algorithm is that it doesn’t need to generate conditional pattern bases and subconditional pattern tree recursively.In order to overcome the disadvantages of Apriori algorithm and efficiently mine association rules without generating candidate itemsets,and also the disadvantage of FP-Growth i.e. consumes more memory and performs badly with long pattern data sets. Now in this paper, an algorithm named Apriori-Growth based on Apriori algorithm and FP-Growth algorithm is proposed, this algorithm can combine the advantages of Apriorialgorithm and FP-Growth algorithm.