Reference : Trustworthy agent-based recommender system in a mobile P2P environment

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a journal
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/25444

Title :	Trustworthy agent-based recommender system in a mobile P2P environment
Language :	English
Author, co-author :	Sahli, N. [Dhofar University, Salalah, Oman]
	Lenzini, Gabriele [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) >]
	Eertink, H. [Novay, P.O. Box 589, Enschede 7500 AN, Netherlands]
Publication date :	2012
Journal title :	Lecture Notes in Computer Science
Volume :	6573 LNAI
Pages :	59-70
Peer reviewed :	Yes
On invitation :	No
Audience :	International
ISSN :	03029743
Event name :	8th International Workshop on Agents and Peer-to-Peer Computing, AP2PC 2009
Event date :	11 May 2009 through 11 May 2009
Event place (city) :	Budapest
Keywords :	[en] Agent based ; Context-Aware ; Limited bandwidth ; Mobile environments ; Mobile P2P ; Multi agent system (MAS) ; P2P system ; Target systems ; Unobtrusiveness ; User intervention ; Wireless traffic ; Distributed computer systems ; Mobile devices ; Multi agent systems ; Recommender systems ; Peer to peer networks
Abstract :	[en] Current major P2P systems focus on PCs and do not provide services for the mobile environment. Compared to traditional P2P, characteristics of Mobile P2P include unreliable connections, limited bandwidth and constraints of mobile devices. In addition, nomadic users demand applications and services that are context-aware, personalised, secure, and trustworthy. Recommender systems are one of these applications. In this paper, we aim at building a mobile P2P recommender system which dramatically reduces wireless traffic between peers, brings trustworthiness (each peer can choose to rely on opinions of peers whom he trusts), and ffers unobtrusiveness (the target system is mainly autonomous and requires a minimum user intervention). Our solution is based on multi-agent systems and is illustrated on a slow-food restaurant recommender system. © 2012 Springer-Verlag.
Permalink :	http://hdl.handle.net/10993/25444
DOI :	10.1007/978-3-642-31809-2_6
Commentary :	92173 9783642318085

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