Title :
Mining Maximal Frequent Access Sequences Based on Improved WAP-tree
Author :
Tan Xiaoqiu ; Yao Min ; Zhang Jianke
Author_Institution :
Coll. of Inf., Zhejiang Ocean Univ., Zhoushan
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
Keywords :
Internet; data mining; WAP-tree; Web access pattern tree; Web usage data; Web usage mining; highly compressed access sequences; maximal frequent access sequence mining; sequential pattern mining; transaction database; user access pattern analysis; Computer science; Educational institutions; Frequency; Information analysis; Oceans; Pattern analysis; Space technology; Transaction databases; Tree data structures; Web mining; Maximum Access Sequence; Restrained sub-tree; Sequential pattern mining; Web Access pattern tree; Web Usage Mining;
Conference_Titel :
Intelligent Systems Design and Applications, 2006. ISDA '06. Sixth International Conference on
Conference_Location :
Jinan
Print_ISBN :
0-7695-2528-8
DOI :
10.1109/ISDA.2006.193
