The generation of the frequent item linked list set is a main problem in the association rules data mining.

Based on a new idea of frequent item table which can be directly used in fast frequent mode mining,an effective FP_growth mining algorithm is presented in this paper.

A Fast Algorithm for Mining Maximum Frequent Item Sets;

A frequent itemsets mining algorithm based on set;

Algorithm for mining maximal frequent itemsets based on FP-tree;

Research on frequent itemsets based on SQL;

Mining algorithm of association rule based on frequent itemsets candidate;

Algorithm based on adjacent lattice for finding frequent itemsets;

Multi-subjected clustering algorithm based on frequent itemsets;

Research on frequent item sets discovery algorithm Apriori;

An efficient algorithm, RIFCI, for mining association rule, is proposed by simultaneously mining the frequent closed item sets instead of traditional frequent item sets and at the mean time exploring both the item set space and transaction space, as is distinguished from all previous association mining methods that exploit only the item set search space.