Incremental sequential pattern mining algorithms of Web site access in grid structure database

被引：4

作者：

Liu, Dawei ^{[1
]}

Cai, Saifeng ^{[1
]}

Guo, Xiaohong ^{[1
]}

机构：

[1] Hangzhou Dianzi Univ, Sch Management, 1st,2nd Ave Xiasha Educ Zone, Hangzhou 310018, Zhejiang, Peoples R China

来源：

NEURAL COMPUTING & APPLICATIONS | 2017年 / 28卷 / 03期

关键词：

Data mining; Sequential pattern mining; Web log; Web access pattern; Grid structure; REVERSE LOGISTICS;

D O I：

10.1007/s00521-015-2096-4

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Sequential pattern mining is a process of knowledge discovery which finds the frequent subsequence as a mode from the sequence database. Web log database is typically dynamic. Web log records are generated constantly, and user access patterns will change accordingly. This study focused on taking advantage of the dynamic characteristics of the Web access database, delivering a fast and efficient incremental mining algorithm. An IncWTP algorithm suitable for Web access sequence mode is developed to handle non-simple path with dynamic data storage structure, and detect and delete the failed sequence data timely.

引用

页码：575 / 583

页数：9

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