Prediction of User's Web-Browsing Behavior: Application of Markov Model

2012 ◽  
Vol 42 (4) ◽  
pp. 1131-1142 ◽  
Author(s):  
M. A. Awad ◽  
I. Khalil
Keyword(s):  
Markov Model ◽  
Web Browsing ◽  
Browsing Behavior

HTTP-sCAN: Detecting HTTP-flooding attack by modeling multi-features of web browsing behavior from noisy web-logs

2015 ◽  
Vol 12 (2) ◽  
pp. 118-128 ◽  
Author(s):  
Jin Wang ◽  
Min Zhang ◽  
Xiaolong Yang ◽  
Keping Long ◽  
Jie Xu
Keyword(s):  
Web Browsing ◽  
Flooding Attack ◽  
Web Logs ◽  
Browsing Behavior

Influencing web-browsing behavior with intriguing and informative hyperlink wording

2005 ◽  
Vol 31 (5) ◽  
pp. 433-445 ◽  
Author(s):  
Carolyn Y. Wei ◽  
Mary B. Evans ◽  
Matthew Eliot ◽  
Jennifer Barrick ◽  
Brandon Maust ◽  
...  
Keyword(s):  
Web Browsing ◽  
Browsing Behavior

scholarly journals Web browsing behavior analysis and interactive hypervideo

2013 ◽  
Vol 7 (4) ◽  
pp. 1-28 ◽  
Author(s):  
Luis A. Leiva ◽  
Roberto Vivó
Keyword(s):  
Behavior Analysis ◽  
Web Browsing ◽  
Browsing Behavior

scholarly journals Reinforcement Learning Page Prediction for Hierarchically Ordered Municipal Websites

Information ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 231
Author(s):  
Petri Puustinen ◽  
Kostas Stefanidis ◽  
Jaana Kekäläinen ◽  
Marko Junkkari
Keyword(s):  
Reinforcement Learning ◽  
Learning Approach ◽  
Electronic Document ◽  
Training Algorithm ◽  
Web Browsing ◽  
Accurate Predictor ◽  
Document Repositories ◽  
Browsing Behavior

Public websites offer information on a variety of topics and services and are accessed by users with varying skills to browse the kind of electronic document repositories. However, the complex website structure and diversity of web browsing behavior create a challenging task for click prediction. This paper presents the results of a novel reinforcement learning approach to model user browsing patterns in a hierarchically ordered municipal website. We study how accurate predictor the browsing history is, when the target pages are not immediate next pages pointed by hyperlinks, but appear a number of levels down the hierarchy. We compare traditional type of baseline classifiers’ performance against our reinforcement learning-based training algorithm.

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