Self adapting websites: mining user access logs.
Professor Susan Craw firstname.lastname@example.org
The Web can be regarded as a large repository of diversified information in the form of millions of websites distributed across the globe. However, the ever increasing number of websites in the Web has made it extremely difficult for users to find the right informa- tion that satisfies their current needs. In order to address this problem, many researchers explored Web Mining as a way of developing intelligent websites, which could present the information available in a website in a more meaningful way by relating it to a users need. Web Mining applies data mining techniques on web usage, web content or web structure data to discover useful knowledge such as topical relations between documents, users access patterns and website usage statistics. This knowledge is then used to develop intelligent websites that can personalise the content of a website based on a users prefer- ence. However, existing intelligent websites are too focussed on filtering the information available in a website to match a users need, ignoring the true source of users problems in the Web. The majority of problems faced by users in the Web today, can be reduced to issues related to a websites design. All too often, users needs change rapidly but the websites remain static and existing intelligent websites such as customisation, personalisa- tion and recommender systems only provide temporary solutions to this problem. An idea introduced to address this limitation is the development of adaptive websites. Adaptive websites are sites that automatically change their organisation and presentation based on users access patterns. Shortcutting is a sophisticated method used to change the organi- sation of a website. It involves connecting two documents that were previously unlinked in a website by adding a new hyperlink between them based on correlations in users visits. Existing methods tend to minimize the number of clicks required to find a target document by providing a shortcut between the initial and target documents in a users navigational path. This approach assumes the sequence of intermediate documents appearing in the path is insignificant to a users information need and bypasses them. In this work, we explore the idea of adaptive websites and present our approach to it using wayposts to address the above mentioned limitation. Wayposts are intermediate documents in a users path which may contain information significant to a users need that could lead him to his intended target document. Our work identifies such wayposts from frequently travelled users paths and suggests them as potential navigational shortcuts, which could be used to improve a websites organisation.
BATHUMALAI, G. 2008. Self adapting websites: mining user access logs. Robert Gordon University, MRes thesis.
|Deposit Date||Nov 17, 2008|
|Publicly Available Date||Nov 17, 2008|
|Keywords||Web mining; Wayposts; Adaptive websites|
BATHUMALAI 2008 Self adapting websites
Publisher Licence URL
Copyright: the author and Robert Gordon University
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