A Fast Algorithm of Mining Multidimensional Association Rules Frequently

In this paper, a novel algorithm named MDFM is proposed. It is an algorithm for mining multidimensional association rules frequently from relational database. The algorithm uses a structure including many indexes and bases on statistic idea. When using the algorithm for the first time, it scans the target database only once and all frequent itemsets and association rules can be generated. After some parameters are adjusted, it is not necessary to scan the database at all and all frequent itemsets can be generated when the algorithm runs again. So, it can be used when the target database must be mined time after time. Compared with some traditional algorithms of mining association rules, the algorithm presented in this paper has better executive efficiency and expansibility, which is proved in our experiments