THE RESEARCH OF MAXIMAL FREQUENT ITEMSET INCREMENT UPDATED MINING ALGORITHMS

摘要

Association rule mining is a important field of data mining and mining maximal frequent itemset is a better solution for mining association rules, but with the data added, the most algorithms can't discover updated maximal frequent itemset efficiently. In this paper an increment updated algorithm MFIIUM is developed by using the maximal frequent itemset mined to reduce the problem space efficiently. At last we perform an experiment on a real dataset to test the algorithms. The experiment show that MFIIUM is efficient for mining updated maximal frequent itemsets.