ARS: web page recommendation system for anonymous users based on web usage mining

Authors:
Yahya AlMurtadha;MD. Nasir Bin Sulaiman;Norwati Mustapha;Nur Izura Udzir;Zaiton Muda
Affiliations:
University Putra Malaysia, Selangor, Malaysia;University Putra Malaysia, Selangor, Malaysia;University Putra Malaysia, Selangor, Malaysia;University Putra Malaysia, Selangor, Malaysia;University Putra Malaysia, Selangor, Malaysia
Venue:
ECS'10/ECCTD'10/ECCOM'10/ECCS'10 Proceedings of the European conference of systems, and European conference of circuits technology and devices, and European conference of communications, and European conference on Computer science
Year:
2010

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Abstract

Web now becomes the backbone of the information. Today the major concerns are not the availability of information but rather obtaining the right information. Mining the web aims at discovering the hidden and useful knowledge from web hyperlinks, contents or usage logs. This paper focuses on improving the prediction of the next visited web pages and recommends them to the current anonymous user based on web usage mining technique where many data mining techniques applied to web server logs. We proposed ARS to recommend to the anonymous web user by assigning him to the best navigation profiles obtained by previous navigations of similar interested users based on his early stage navigation. To represent the anonymous user's navigation history, we used a window sliding method with size n over his current navigation session. Using CTI dataset the experimental results show higher prediction accuracy for the next visited pages for anonymous users compared to previous recommendation system.