Presented a problem of mining maximal frequent itemsets with constrained itemsets-length and generating corresponding transaction information of itemsets,which is defined as L-MAX frequent itemsets mining.

Mining of maximum frequent itemsets and frequent closed itemsets based on frequent itemsets;

Algorithm of Mining Frequent Itemsets Based on Binary Representation;

Algorithm for frequent item sets mining of sharing prefix based on FP-tree

Algorithm for Mining Frequent Item Sets Based on Genetic Particle Swarm Optimization

A new algorithm FIS-Miner(Frequent Item Sets Miner) is presented for discovering frequent item sets to decrease candidate generation based on vector matrix.

Representation and mining of frequent itemsets based on the pruned concept lattice;

Representation and mining of frequent itemsets based on multiple pruned concept lattices;

Efficient algorithm of mining weighted frequent itemsets based on matrix and bit string;

Applying the hierarchical sketch,an algorithm that finds hierarchical frequent items over data streams dynamically and approximately was implemented.

Due to the irreversibility of random hash mapping,current sketch data structures have to traverse the key address space to find frequent items.

It s been found the efficiency of algorithms can been improved by pruning the candidate items C_k based on frequent items L_(k-1),and ignoring the transactions which is useless for frequent items generated.

Research on Mining Algorithms of Maximal Frequent Item Sets;

Making over the FP-tree structure,the frequent item set of mining algorithm called UPM is preposed.

Aiming at the problem of data association rules mining about late years,this paper introduces vector inner product to the field and raises generating efficiency of database frequent item sets with equitable data store structure.