The Community for Technology Leaders
RSS Icon
Venice/Mestre, Italy
May 24, 2009 to May 28, 2009
ISBN: 978-0-7695-3613-2
pp: 90-96
In this paper, we present {\sc Cobras}: a CBR-based Peer-to-Peer bibliographical reference recommender system. The system allows a group of like-minded people to share their bibliographical data in an implicit and intelligent way. The system associates a software agent with each user. Agents are attributed three main skills: a) detecting the associated user hot topics, b) selecting a subset of peer agents that are likely to provide relevant recommendations and c) recommending both documents and other agents in response to a recommendation request sent by a peer agent. The last two skills are handled by two inter-related data-driven case-based reasoning sub-systems. This paper focuses on the design and the implementation of these two sub-systems. An experimental study involving one hundred software agents using real bibliographical data is described. Obtained results assess the validity of the proposed approach.
Recommender systems, P2P, Case-based reasoning
Rushed Kanawati, Hager Karoui, "A P2P Collaborative Bibliography Recommender System", ICIW, 2009, Internet and Web Applications and Services, International Conference on, Internet and Web Applications and Services, International Conference on 2009, pp. 90-96, doi:10.1109/ICIW.2009.113
30 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool