计算机与现代化 ›› 2011, Vol. 1 ›› Issue (3): 17-20.doi: 10.3969/j.issn.1006-2475.2011.03.006

• 人工智能 • 上一篇    下一篇

改进的FLWAP的Web访问序列模式挖掘方法

王海波1,陈志国1,徐一秋1,李朋轩2   

  1. 1.牡丹江医学院教育技术与信息中心,黑龙江 牡丹江 157011;2.阿里巴巴(中国)网络技术有限公司,浙江 杭州 310099
  • 收稿日期:2010-10-22 修回日期:1900-01-01 出版日期:2011-03-18 发布日期:2011-03-18

Improved Mining Method for FLWAP on Web Access Sequential Pattern

WANG Hai-bo1, CHEN Zhi-guo1, XU Yi-qiu1, LI Peng-xuan2   

  1. 1. Center of Educational Technology and Information, Mudanjiang Medical University, Mudanjiang 157011, China;2. Alibaba (China) Network Technology Co., Ltd., Hangzhou 310099, China
  • Received:2010-10-22 Revised:1900-01-01 Online:2011-03-18 Published:2011-03-18

摘要: 为了提高序列模式挖掘的FLWAP-mine算法挖掘海量数据的效率和性能,基于减少数据库访问次数原则和序列模式的Apriori性质对FLWAP-mine算法进行改进,构造FLWAP-tree过程中只扫描一次访问序列数据库,对树进行剪枝删除非频繁事件。模式挖掘过程中采取投影数据库思想,只搜索当前模式的投影树,对构造的投影树判断剪枝,去除非频繁事件,进一步缩小搜索范围。实验表明,当数据量较大或支持度阈值较小时,改进的FLWAP-mine算法比FLWAP-mine算法有更好的性能。

关键词: 序列模式, FLWAP-mine, 投影树, 剪枝

Abstract: In order to improve the efficiency and performance of mass data mining for FLWAP-mine algorithm, based on reducing the time of scanning the database and the Apriori properties of sequential pattern, the FLWAP-mine algorithm is improved. It constructs the projection tree by scanning the database once, and then deletes the non-frequent events from the projection tree by pruning. The improved FLWAP-mine algorithm adopts the idea of the projection tree to search the projection tree of the current pattern, reduces the search area by pruning the projection tree. The experimental results show that the improved FLWAP-mine algorithm performs better than the previous one when the data set is large or the minimum support threshold is small.

Key words: sequential pattern, FLWAP-mine, projection tree, pruning

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