序列模式挖掘研究  

Sequential Pattern Mining Research

作　　者：吴孔玲[1] 缪裕青[1] 苏杰[1] 张晓华[1] 

机构地区：[1]桂林电子科技大学计算机科学与工程学院,桂林541004

出　　处：《计算机系统应用》2012年第6期263-271,共9页Computer Systems & Applications

摘　　要：为了更好地分析购物篮数据,挖掘出潜在客户,序列模式挖掘应运而生。序列模式挖掘是数据挖掘一个重要研究内容,近年来在很多领域得到广泛运用。概述序列模式挖掘的发展现状,研究基本挖掘框架的经典挖掘算法与扩展模型挖掘算法,特别针对近年来出现的新数据形式序列模式挖掘,以及基于零压缩二叉决策图(ZBDD)结构的挖掘算法做了阐述,最后对序列模式挖掘发展趋势进行了展望。In order to analysis shopping basket data better, mine potential customers, sequential pattern minging emerged.Sequential pattern mining is an important research content of data mining and has been widely used in many fields in recent years. We summary sequential pattern mining development situation at present, research classical algorithm based on basic mining framework and algorithm based on extension model, Especially describe the new data form sequential pattern mining appeared in recent years and the algorithm based on zero compression binary decision figure （ZBDD）, Finally prospect the sequential pattern mining development trend.

关 键 词：序列模式挖掘 模式增长 投影数据库 零压缩二叉决策图 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]