摘要：Narrowing down the computational space is a key factor in improving the efficiency of an association rule mining system. One approach to achieve this is to let the user guide the association rule mining process by enabling the user to specify the types of association rules that he/she might be interested in. Instead of computing all that can be computed, the system limits its association rule mining process to the discovery of only the association rules that may be of interest to the user, therefore, reducing the computational space and complexity. In this paper, we introduce a new approach for achieving this by using a new structure called lattice intension structure.
