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Web personalization is the process of customizing a Web site to the needs of specific users, taking advantage of the knowledge acquired from the analysis of the user’s navigational behaviour (usage data) in correlation with other information collected in the Web context, namely structure, content and user profile data. ISPs have full knowledge of the visited Web graph by all the subscribers-navigational patterns and all users’ demographic and context related data can add Recommendations in every web page the user visits in real time. This gives a potential for an ISP Advertising framework (targeted), as effective as Google ad-words. The proposed system for personalization on the web will be implemented in the internet provider and offer the ability to provide real time personalization services to customers. The system will collect information concerning the navigation and preferences of users as they are browsing the Internet. By utilizing usage-data, data mining techniques and learning procedures, user profiles will be created as well as appropriate sets of recommendations that will be related both to their interests and the website they visit at the time. Recommendations will be introduced real time into the content as traffic is passing through telecom devices (i.e. routers) the user in order to achieve a more effective browsing and increase potential sales of advertising revenues.
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