Web recommendation systems: the case of on-line trade fairs

Abstract

A good deal of current research in Web-based applications is aimed at enabling an application to adapt its own behavior to the users characteristics, such as goals, tasks, interests, that are stored in user profiles. We describe the personalisation component we have implemented in FAIRWIS, a system that offers on-line innovative services to support the management of real trade fairs as well as Web-based virtual fairs. Our approach integrates the data the system collects about users, both explicitly and implicitly, and a classical collaborative filtering technique in order to provide recommendations to the user during the visit of the on-line fair catalogue

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