Prediction of Web User’s Browsing Behavior using All Kth Markov model and CSB-mine

International Journal of Computer Trends and Technology (IJCTT)          
© 2017 by IJCTT Journal
Volume-43 Number-1
Year of Publication : 2017
Authors : Neha V. Patil, Dr. Hitendra D.Patil
DOI :  10.14445/22312803/IJCTT-V43P110


Neha V. Patil, Dr. Hitendra D.Patil  "Prediction of Web User’s Browsing Behavior using All Kth Markov model and CSB-mine". International Journal of Computer Trends and Technology (IJCTT) V43(1):68-74, January 2017. ISSN:2231-2803. Published by Seventh Sense Research Group.

Abstract -
Web Usage Mining (WUM) provides interesting rules and patterns of user web browsing behavior and prediction technique is very useful where the next set of web pages are predicted based on history of visited web pages. Nowadays use of the web and so the internet traffic has increased, so prediction of user web behavior plays important role in various applications like smart phones, recommendation systems and web personalization, etc. Various prediction models have been proposed based on Markov models, Association Rule Mining (ARM), etc. The Specific order of the Markov model cannot predict for a session that was not observed previously in the training set. ARM endures scalability issue, originates from generating item sets. Proposed system first preprocess raw web log, construct sessions for different users, then All Kth Markov model and using Conditional Sequence Base (CSB-mine), Sequential Access Patterns based model both are used individually to predict the next page that a user may visit.

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WUM, Web session, Web browsing behavior, web prediction, All Kth Markov, CSB-mine