计算机应用研究2017，Vol.34Issue(1)：128-131,140,5.DOI:10.3969/j.issn.1001-3695.2017.01.027
基于时间衰减模型的模糊会话关联规则挖掘算法
Fuzzy session association rule mining algorithm based on time decay model
摘要
Abstract
The existing algorithms do not consider the non-uniform distribution feature of session and the effect of historical data in association rule mining.It also cannot handle the sharp boundaries problem of continuous attributes.As to solve these problems,this paper proposed a fuzzy session association rule mining algorithm based on time decay model.First,for the non-uniform distribution feature of data stream session,it used the time slice to divide the data stream for retaining the relevant re-lationship information of sessions.Then,applied the fuzzy set to discrete continuous attributes,increasing the interestingness and comprehensibility of the rules.Finally,it used the time decay factor and error factor in fuzzy association rules mining. And experimental results show that this method has obvious advantages in improving time efficiency,reducing redundancy and increasing the interest of rules.关键词
数据流/时间片/关联规则/模糊集/衰减模型Key words
data stream/time slice/association rules/fuzzy sets/decay model分类
信息技术与安全科学引用本文复制引用
杨英杰,邱卫..基于时间衰减模型的模糊会话关联规则挖掘算法[J].计算机应用研究,2017,34(1):128-131,140,5.基金项目
国家“863”计划资助项目（2012AA012704）；国家“973”计划资助项目（2011CB311801）；郑州市科技领军人才项目 （）
