Visual Mining of Web Logs with DataTube2

Author(s):  
Florian Sureau ◽  
Frederic Plantard ◽  
Fatma Bouali ◽  
Gilles Venturini
Keyword(s):  
Science ◽  
2006 ◽  
Vol 312 (5779) ◽  
pp. 1447b-1447b
Keyword(s):  

Warta LPM ◽  
2017 ◽  
Vol 13 (1) ◽  
pp. 11-19
Author(s):  
Azizah Fatmawati

Web is one medium that can be used by many activists in communityorganizations to actualize themselves and communicate effectively. Web UtilizationTraining for Muhammadiyah Youth in Kartasura branch is expected to provideknowledge into the importance of mastering Information Technology and increasethe understanding of the web (Web Logs) as the more effective information tool (AmarMa’ruf Nahi Munkar). The result shows that the implementation of the training isquite successful. This can be seen from the enthusiasm of the participants in providingfeedback from the questionnaires delivered before and after the training. Furthermore,the training also shows an increasing knowledge in the use of the web as much as64%.


Author(s):  
Qiang Yang ◽  
Henry Haining Zhang ◽  
Ian T. Y. Li ◽  
Ye Lu
Keyword(s):  

Web Mining ◽  
2011 ◽  
pp. 322-338 ◽  
Author(s):  
Zhixiang Chen ◽  
Richard H. Fowler ◽  
Ada Wai-Chee Fu ◽  
Chunyue Wang

A maximal forward reference of a Web user is a longest consecutive sequence of Web pages visited by the user in a session without revisiting some previously visited page in the sequence. Efficient mining of frequent traversal path patterns, that is, large reference sequences of maximal forward references, from very large Web logs is a fundamental problem in Web mining. This chapter aims at designing algorithms for this problem with the best possible efficiency. First, two optimal linear time algorithms are designed for finding maximal forward references from Web logs. Second, two algorithms for mining frequent traversal path patterns are devised with the help of a fast construction of shallow generalized suffix trees over a very large alphabet. These two algorithms have respectively provable linear and sublinear time complexity, and their performances are analyzed in comparison with the a priori-like algorithms and the Ukkonen algorithm. It is shown that these two new algorithms are substantially more efficient than the a priori-like algorithms and the Ukkonen algorithm.


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