Robust framework for recommending restructuring of websites by analysing web usage and web structure data
Mohamad Nagi, Ahmad Elhajj, Omar Addam, Ala Qabaja, Omar Zarour, Tamer N. Jarada, Shang Gao, Jamal Jida, Ayman N. Murshed, Iyad Sleiman, Tansel Özyer, Mick J. Ridley, Reda Alhajj · International Journal of Business Intelligence and Data Mining · 2012
The work described in this paper is motivated by the fact that the structure of a website may not satisfy a larger population of the visiting users who may jump between pages of the website before they land on the target page(s); this is at least partially true because access patterns were not known when the website was designed. We developed a robust framework that tackles this problem by considering both web log data and web structure data to suggest a more compact structure that could satisfy a larger user group. The study assumes the trend recorded so far in the web log reflects well the anticipated behaviour of the users in the future. We separately analyse web log and web structure data using three techniques, namely clustering, frequent pattern mining and network analysis. The final outcome from the two stages is reflected on to one of the six models, namely the network of pages to report linking pages by the most appropriate connections.