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CAISE
2003
Springer

Recommendation Based Discovery of Dynamic Virtual Communities

9 years 3 months ago
Recommendation Based Discovery of Dynamic Virtual Communities
Recommendation systems are becoming increasingly popular in various large-scale web-based applications (such as infomediaries, emarketplaces, knowledge portals) since they enable users and customers to better fulfil their information or product search needs according to their interests. Techniques used to form the recommendations include algorithms from the area of machine learning and vote theory. We introduce an alternative way of building user profiles based on explicit and implicit ratings as well as profile-based recommendation and user-matching algorithms. The paper advocates the use of such algorithms as a tool to automate the discovery and creation of dynamic, virtual communities. Furthermore, rating prediction algorithms are proposed as a means of enhancing the interaction between users and a recommendation system. As an application of the proposed techniques, we present MRS, a web-based information system that provides personalized recommendations for cinema movies.
Manos Papagelis, Dimitris Plexousakis
Added 06 Jul 2010
Updated 06 Jul 2010
Type Conference
Year 2003
Where CAISE
Authors Manos Papagelis, Dimitris Plexousakis
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