摘要
为了有效地挖掘物流管理系统中的物流频繁路径序列模式,提出了一种针对物流数据分析的路径序列挖掘算法ImGSP算法.ImGSP算法通过对原始路径数据库筛选,选出路径序列长度大于或等于候选序列长度的路径序列,有针对性地产生过度候选序列,来约减候选序列.实验结果表明:ImGSP算法能够有效地减少候选序列数量,生成频繁路径序列模式,进而产生物流中有用的规则.该方法不仅缩小了扫描数据库的规模,而且减少了生成频繁序列的候选序列集合.
Currently the data in logistic system is very huge,so the efficiency of mining frequent path sequences needs to be improved.Therefore,an efficient algorithm-ImGSP（improved generalized sequential patterns）for analyzing logistic data is presented.In this method the original database is screened to find the path sequences that is greater than or equal to the candidate sequences in the length,and then generate the candidate sequences through generating the transitional candidate sequences.The experiment results show that the ImGSP algorithm can effectively generate frequent patterns by reducing the volume of sequences,and then find the valuable rules.The method not only reduces the size of scanning database but also reduces the candidate sequences set.
出处
《东南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2008年第6期970-974,共5页
Journal of Southeast University：Natural Science Edition
基金
国家自然科学基金资助项目(60773103,60673060,70772059)
中国博士后科学基金资助项目(20070420954)
江苏省“青蓝工程”基金资助项目.
关键词
物流管理系统
数据挖掘
关联规则
序列模式挖掘
logistic management system
data mining
association rules
sequential patterns mining
