基于加权关联规则的护理人员职场偏差行为研究  

On the Research of Nurses' Workplace Deviance Behavior Based on Weighted Association Rules

作　　者：王冬燕[1] 余嘉元[1] 

机构地区：[1]南京师范大学心理学系,江苏南京210097

出　　处：《微电子学与计算机》2012年第3期117-120,共4页Microelectronics & Computer

摘　　要：利用加权关联规则方法提取护理人员职场偏差行为问卷研究中的规则,样本包括539名护理人员.鉴于偏差行为影响因素重要性的不一致,基于传统的关联规则Apriori算法,设计并实现了加权关联规则的挖掘算法,应用于护理人员偏差行为的研究.实验表明,与Apriori算法相比,加权关联规则方法提取出更多的规则,并且可以增强某些规则的支持度和置信度,使这些规则更容易被发现,说明该方法是可行的.Weighted association rules is applied to extract the rules in the questionnaire of the nurses＇ workplace deviant behavior.The sample includes 539 nurses.According to the importance of factors that influence workplace deviant behavior is inconsistent,based on the traditional Apriori algorithm for association rules,designing and implementing the mining algorithm of weighted associationg rules,to applied to the research of nurses＇ workplace deviant behavior.It was shown that,compared with the Apriori algorithm,weighted association rules can extract more rules,and enhance the support and confidence of some of the rules,to make the rules easier to find.It shows that the method is feasible.

关 键 词：APRIORI算法 加权关联规则 职场偏差行为 护理 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]