Website link prediction using a Markov chain model based on multiple time periods Online publication date: Tue, 16-Jan-2007
by Shantha Jayalal, Chris Hawksley, Pearl Brereton
International Journal of Web Engineering and Technology (IJWET), Vol. 3, No. 3, 2007
Abstract: Growing size and complexity of many websites have made navigation through these sites increasingly difficult. Attempting to automatically predict the next page for a website user to visit has many potential benefits, for example in site navigation, automatic tour generation, adaptive web applications, recommendation systems, web server optimisation, web search and web pre-fetching. This paper describes an approach to link prediction using a Markov chain model based on an exponentially smoothed transition probability matrix which incorporates site usage statistics collected over multiple time periods. The improved performance of this approach compared to earlier methods is also discussed.
Online publication date: Tue, 16-Jan-2007
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Web Engineering and Technology (IJWET):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email email@example.com