Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/5933
Title: Robust framework for recommending restructuring of websites by analysing web usage and web structure data
Authors: Nagi, M.
Elhajj, A.
Addam, O.
Qabaja, A.
Zarour, O.
Jarada, T.
Alhajj, Reda
Keywords: Clustering
Frequent pattern mining
Network analysis
Web log
Web structure mining
Web usage mining
Issue Date: 2012
Publisher: Inderscience Publishers
Abstract: 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. Copyright © 2012 Inderscience Enterprises Ltd.
URI: https://doi.org/10.1504/IJBIDM.2012.048725
https://hdl.handle.net/20.500.11851/5933
ISSN: 1743-8187
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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