Paper Info
Title
Mining Maximal Frequent Access Sequences Based on Improved WAP-tree
Abstract
It is worthwhile to analyze user's access patterns by capturing maximal access sequences from web usage data in practice. Web Access Pattern Tree (WAP-tree) stores the highly compressed access sequences, and mining frequent access sequences based on WAP-tree needs to scan transaction database only twice. However, producing conditional WAP-tree repeatedly in the algorithm influences the efficiency in a certain degree. Considering the shortage of WAP-tree, combined with the need of mining maximal access sequences, this paper improves WAP-tree and introduces restrained sub tree structure to solve the problem that a mass of conditional WAP-tree is built in the traditional algorithm. In addition, restrained sub trees inherit the nodes of WAP-tree so that memory is saves. The results of experiments show the efficiency of the improved algorithm.
Year
DOI
Venue
2006
10.1109/ISDA.2006.193
ISDA
Keywords
Field
DocType
web usage mining, web access pattern tree, restrained sub-tree, maximum access sequence, sequential pattern mining
Data mining,Web mining,Computer science,Web access pattern,Tree structure,Web usage data,Database transaction,Economic shortage,Sequential Pattern Mining,The Internet
Conference
ISBN
Citations 
PageRank 
0-7695-2528-8
1
0.36
References 
Authors
0
3
Name
Order
Citations
PageRank
Xiaoqiu Tan1111.65
Min Yao2253.82
Jianke Zhang314510.23