A top-down algorithm for mining web access patterns from web logs

被引：0
|
作者：
Guo, JK [1 ]
Ruan, BJ
Cheng, ZP
Su, FZ
Wang, YQ
Deng, XB
Shang, N
Zhu, YY
机构：
[1] Fudan Univ, Dept Comp Sci, Shanghai 200433, Peoples R China
[2] Fuzhou Univ, Dept Comp Sci, Fuzhou 350002, Peoples R China
来源：
ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PROCEEDINGS | 2005年 / 3518卷
关键词：
sequential mining; web mining; web usage mining; web access pattern; P-tree database;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper proposes a new algorithm, called TAM-WAP(the shorthand for Top-down Algorithm for Mining Web Access Patterns), to mine interesting WAP from Web logs. TAM-WAP searches the P-tree database in the top-down manner to mine WAR By selectively building intermediate data according to the features of current area to be mined, it can avoid stubbornly building intermediate data for each step of mining process. The experiments for both real data and artificial data show that our algorithm outperforms conventional methods.
引用
收藏
页码：838 / 843
页数：6
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