摘要：Sequential association rule mining is one of the possible methods to analysis of data. As conventional sequential association rule mining very often generates a huge number of association rules, of which many are redundant, it is desirable to find a solution to get rid of those unnecessary association rules, because of the complexity and temporal ordered characteristics of sequential data, current research of sequential rule mining is limited. Although several sequential association rule prediction model using either sequence constraint or temporal constraint have been proposed, none of them considered the redundancy problem in rule mining. The main purpose of this paper to propose a non redundant sequential association rule mining method proposed the Sequential Min-Max basis for concise representation of non-redundant sequential association rules.
