Abstract: To efficiently process mass transactions with temporal attribute, the key time interval ( KhI)，the minimum time interval reflecting correlation of items was introduced. A maximum clique based KTI mining algorithm was proposed, which reduces the complexity for information mining and decision making. Assuming the probability distribution of items is uniform for the target transaction, we stated an approach to find the KhI of the transaction and analyzed the correctness and complexity of the method. Experiments show that through considering the KTI of a clique, the candidates set impacting the accuracy of decision is reduced, and the resource consumption is saved mainly. In the end, we evaluated the feasibility of the proposed method in the real world use.

Key words: Data mining, Association rule, Time series logic, Maximum clique, Key time interval(KTI) , Probability