计算机应用与软件2018，Vol.35Issue(1)：269-275,7.DOI:10.3969/j.issn.1000-386x.2018.01.047
多支持度下用户行为序列模式挖掘方法研究
RESEARCH ON MINING USER BEHAVIOR SEQUENTIAL PATTERNS WITH MULTIPLE SUPPORTS
摘要
Abstract
Aiming at the limitation of the single support threshold of most current sequential pattern mining methods,a sequential pattern mining method with multiple minimum supports based onprefix tree structure was proposed.We designed a prefix tree structure MSLP-tree with multiple supports and proposed a sequential pattern growth algorithm based on this structure,which was called MSLP-growth.The algorithm obtained the precise frequent sequential patterns by considering the varied minimum support of each item.In the premise of ensuring the accuracy and integrity of the mining results,the storage space was greatly reduced and the search time was shortened.Experimental results showed that compared with MS-GSP algorithm,MSLP-growth algorithm had higher mining efficiency and scalability.关键词
行为模式/序列模式挖掘/多支持度/前缀树Key words
Behavior profiles/Sequence pattern mining/Multiple supports/Prefix tree分类
信息技术与安全科学引用本文复制引用
徐启寒,徐开勇,郭松,戴乐育..多支持度下用户行为序列模式挖掘方法研究[J].计算机应用与软件,2018,35(1):269-275,7.基金项目
国家重点研发计划项目(2016YFB0501900). （2016YFB0501900）
