基于OLAP的关联规则挖掘研究与实现

Research and Implementation of Association Rules Mining Based on OLAP

数据挖掘(DM)和联机分析处理(OLAP)是支持企业决策的有效办法。从关联规则挖掘的特点考虑,结合Apriori算法的不足之处,提出改进的频繁项目集RT_Apr算法。引入新的存储单元Tid_unit,大大减少了遍历数据库次数,有效地降低了算法的时间复杂度,构建OLAP与关联规则挖掘集成模型,并在此基础上设计并实现了关联规则挖掘系统,节约了挖掘时间和提高了系统效率。

The data nfining（DM） and on-line analytical processing（OLAP） are the effective ways to support business decisions. In view of the characteristics of association rules mining and the deficiency of Apriori algorithm, this paper puts forward an improved RT_Apr frequent iterusets algorithm. The introduction of new storage unit Tid unit can greatly decrease the times of traverse database and effectively reduce the time complexity of the algorithm. The OLAP and integration model for mining association rules is built, and based on this model, the association rule mining system is designed and implemented for mining time saving and system efficiency improving.