Abstract: Association rules mining with constraints is an important association mining method, and it can mine the rules according to the users needs. Most of algorithms deal with one constraint, but in the reality applications, usually there are two or more constraints. In this paper, a novel algorithm for mining association rules with constraint was proposed.It can deal with two constraints simultaneously, namely constraint of anti-monotone and constraint of monotone. The algorithm consists of three phases, first, frequent 1-itemsets arc collected over the dataset, second, we apply some prune techniques to the constraints check and a conditional database is generated, and at the end, the final frequent itemsets which are satisfied with the constraints are generated. Experimental results show that the proposed algorithm is efficient both in run time and scalability.

Key words: Data mining, Association rules mining, Association rules mining with constraint