User behavior analysis based on user interest by web log mining

2017 ◽  
Author(s):  
Xipei Luo ◽  
Jing Wang ◽  
Qiwei Shen ◽  
Jingyu Wang ◽  
Qi Qi
Keyword(s):  
Behavior Analysis ◽  
User Behavior ◽  
Web Log Mining ◽  
User Interest ◽  
User Behavior Analysis ◽  
Web Log ◽  
Log Mining

DECISION TREES FOR PERNICIOUS PAGES DETECTION

2003 ◽  
Vol 12 (04) ◽  
pp. 527-537 ◽  
Author(s):  
ZIDRINA PABARSKAITE ◽  
JAMES ALLEN LONG
Keyword(s):  
Decision Trees ◽  
User Behavior ◽  
Misclassification Error ◽  
Application Framework ◽  
Web Log Mining ◽  
User Behavior Analysis ◽  
Computational Performance ◽  
Log Mining ◽  
Usage Analysis ◽  
User Actions

An application framework to perform web usage analysis using advanced data mining methodology is presented. The investigation proposes decision trees for web user behavior analysis. This includes prediction of user future actions and the typical pages leading to browsing termination. The widely known decision tree package C4.5 was used in this study. In the new area of web log mining decision trees showed reasonable computational performance and accuracy. Experiments showed that it is possible to predict future user actions with reasonable misclassification error as well as to find combinations of sequential pages resulting in browsing termination. In addition to this, decision trees generate human understandable rules which can be used to analyze further for web site improvement.

Web Log Mining als Controllinginstrument für Online-Shops

Controlling ◽  
2001 ◽  
Vol 13 (3) ◽  
pp. 157-166 ◽  
Author(s):  
Reinhold Mayer ◽  
Frank Bensberg ◽  
Anita Hukemann
Keyword(s):  
Web Log Mining ◽  
Web Log ◽  
Log Mining ◽  
Online Shops

The Research of the Accessibility Website Design Based on Web Log Mining

2012 ◽  
Vol 241-244 ◽  
pp. 2779-2782
Author(s):  
Heng Yao Tang ◽  
Xiao Yan Zhan
Keyword(s):  
Website Design ◽  
Web Log Mining ◽  
Web Page ◽  
Web Log ◽  
User Interests ◽  
Mining Technique ◽  
Dynamic Web ◽  
Log Mining ◽  
The Web

On the problems existing in the realization of current accessibility website, we design a web designing architecture, using the web log mining technique to extract user interests and access priority sequence and adopting the dynamic web page information to fill the web page commonly used structure, realize the intelligent , personalized accessibility.

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