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Mining Web Navigation Profiles For Recommendation System

Author(s): Y.M. AlMurtadha | Md. N.B. Sulaiman | N. Mustapha | N.I. Udzir

Journal: Information Technology Journal
ISSN 1812-5638

Volume: 9;
Issue: 4;
Start page: 790;
Date: 2010;
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Keywords: recommender systems | web usage mining | Usage profiling

This study explores web usage mining, for which many data mining techniques such as clustering, classification and pattern discovery have been applied to web server logs. The output is a set of discovered patterns which form the main input to the recommendation systems which in return predict the next web navigations. Most of the recommendation systems are user-centered which make a prediction list to the users based on their long term navigation history, users databases or full users profiles. Companies wish to attract anonymous users, directed them at the early stages of their visits and get them involved with their websites. Learning and mining the web navigation profiles followed by enhanced classification to the similar activities of previous users will provide an appropriate model to recommend to the current anonymous active user with short term navigation. Using CTI dataset, the experimental results show better prediction accuracy than the previous works. An adaptive profiling to save time is a key fac
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