一种改进的时态关联规则算法  

An Improved Temporal Algorithm of Association Rules

作　　者：陈宫[1] 牛秦洲[1] 

机构地区：[1]桂林理工大学信息科学与工程学院,广西桂林541004

出　　处：《微电子学与计算机》2012年第6期189-192,共4页Microelectronics & Computer

基　　金：广西科学研究与技术开发计划基金项目(桂科攻0992006-1)

摘　　要：针对传统关联规则挖掘中可能会忽略具有时间因素的关联规则的问题,提出了一种具有时间约束的改进时态关联规则算法.该算法通过计算模式平均支持度、数据集平均支持度、模式集中度等参数来判断Apriori算法所得到的模式是否在某一时间区域数据集上具有较高支持度,再对该数据集进行进一步挖掘,以找到更精确的和时间相关的模式,从而得到单个或不同时间区间上的关联规则以及跨时间区间和跨事务的关联规则.通过实验分析,该算法是可行的,并在实际应用中有一定的意义.To question that the association rules with time factor may be neglected in data mining to the traditional related rule, an improved temporal algorithm of association rules with time-constrain is proposed, which first judges if the modes obtained by ＆priori algorithm has relatively high support degree in data set at a certain time region through calculating the average supported-degree of the modes, the average supported-degree of the data set and the concentration degree of the modes, etc. Secondly this algorithm goes on data mining in the data set in order to find more accurate mode correlated with time, thus gets association rules at single time zone or different time zone or acrossing time zone or affairs. Through experimental analysis, this algorithm is feasible, and has certain meanings in practical application.

关 键 词：数据挖掘 时态关联规则 时态数据 支持度 集中度 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]