Deconstructing the Kazaa Network
WIAPP '03 Proceedings of the The Third IEEE Workshop on Internet Applications
Statistical mechanics of complex networks
Statistical mechanics of complex networks
Improving semantic routing efficiency
HOT-P2P '05 Proceedings of the Second International Workshop on Hot Topics in Peer-to-Peer Systems
Characterizing unstructured overlay topologies in modern P2P file-sharing systems
IMC '05 Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement
Evaluating peer-to-peer recommender systems that exploit spontaneous affinities
Proceedings of the 2007 ACM symposium on Applied computing
P2P systems in legal networks: another
Proceedings of the 11th international conference on Artificial intelligence and law
FairPeers: Efficient Profit Sharing in Fair Peer-to-Peer Market Places
Journal of Network and Systems Management
X-hinter: a framework for implementing social oriented recommender systems
Proceedings of the nineteenth ACM conference on Hypertext and hypermedia
MobHinter: epidemic collaborative filtering and self-organization in mobile ad-hoc networks
Proceedings of the 2008 ACM conference on Recommender systems
A peer-to-peer recommender system based on spontaneous affinities
ACM Transactions on Internet Technology (TOIT)
As law goes by: topology, ontology, evolution
AICOL-I/IVR-XXIV'09 Proceedings of the 2009 international conference on AI approaches to the complexity of legal systems: complex systems, the semantic web, ontologies, argumentation, and dialogue
An analysis of peer similarity for recommendations in P2P systems
Multimedia Tools and Applications
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Small World patterns have been found in many social and natural networks, and even in Peer-to-Peer topologies. In this paper, we analyze File Sharing applications that aggregate virtual communities of users exchanging data. In these domains, it is possible to define overlaying structures that we call “Preference Networks” that show self organized interest-based clusters. The relevance of this finding is augmented with the introduction of a proactive recommendation scheme that exploits this natural feature. The intuition behind this scheme is that a user would trust her network of “elective affinities” more than anonymous and generic suggestions made by impersonal entities.