Authors: Omid Kashefi; Mohsen Sharifi; Azadeh Zamanifar
Addresses: School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran ' School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran ' School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran
Abstract: With the ever-increasing infiltration of the internet into everyday affairs of human life, the monitoring and control of social behaviours of users for the purpose of proper management of society has proved prudent. But, most existing approaches to social behaviour analysis are static and fall short of considering the varieties and differences in cultures and localities. We propose a dynamic approach to extract localised users’ favourite websites through logging the URLs that were accessed by users in places such as universities and government institutions; then by categorising the content of logged websites, our categorised users’ favourite websites were created dynamically. We evaluated our approach in a real setting by dynamically building up a database of users’ favourite websites in a six months period operating in the ICT Ministry of Iran. Comparison with famous static URL databases showed the superiority of our approach in catching newly published websites, making our approach more durable in performance.
Keywords: internet usage; personalised information retrieval; URL filtering; content filtering; web inspection; social behaviour analysis; personalisation; website favourites; Iran.
International Journal of Knowledge and Web Intelligence, 2011 Vol.2 No.2/3, pp.157 - 167
Published online: 09 Dec 2011 *Full-text access for editors Access for subscribers Purchase this article Comment on this article