含负项的高效用序列模式挖掘算法  

High Utility Sequential Pattern Mining with Negative Unit Profits

作　　者：吕存伟 黄德才[1] 陆亿红[1] 

机构地区：[1]浙江工业大学计算机科学与技术学院,杭州310023

出　　处：《小型微型计算机系统》2017年第8期1724-1729,共6页Journal of Chinese Computer Systems

基　　金：水利部公益性行业科研专项项目(201401044)资助;国家科技支撑计划子课题项目(2012BAD10B0101)资助

摘　　要：高效用模式挖掘在现实中有广泛的应用,也是数据挖掘研究的热点.数据库中的事务在以序列形式存在的情况下,又引申出高效用序列模式挖掘问题.序列模式的搜索空间比一般模式的大,所以计算复杂度比高效用模式挖掘大.目前对高效用序列模式算法研究比较少,且都没有考虑序列数据库中项的外部效用值为负的情况.面对含负项的外部效用值,首次提出了含负项的高效用序列模式挖掘算法EHUSN,该算法提出1-2-UM和2-2-UM结构模型,结合效用信息列表能快速剪枝非候选序列,从而使挖掘算法在时空效率上的得到提升.Transactions in database in the form of sequence produces high utility sequential pattern mining algorithm. The search space of sequence pattern is bigger than that of normal pattern. So its computational complexity is much bigger. The study of high utility sequential pattern mining algorithm is relatively rare. But not considering the circumstance of the external utility in sequential database is negative. Faced with external utility which includes negative items, the High Utility Sequential pattern mining algorithm EHUSN with negative items is put forward at the first place. It proposes 1-2-UM and 2-2-UM these two structural models on the base of FHM algo- rithm, and the model can prune noncandidate sequence when combined with utility information list,therefore, data mining algorithm is becoming more efficient.

关 键 词：序列模式挖掘 高效用序列模式挖掘 模式挖掘 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]