5,611 research outputs found
Liquid FM: Recommending Music through Viscous Democracy
Most modern recommendation systems use the approach of collaborative
filtering: users that are believed to behave alike are used to produce
recommendations. In this work we describe an application (Liquid FM) taking a
completely different approach. Liquid FM is a music recommendation system that
makes the user responsible for the recommended items. Suggestions are the
result of a voting scheme, employing the idea of viscous democracy. Liquid FM
can also be thought of as the first testbed for this voting system. In this
paper we outline the design and architecture of the application, both from the
theoretical and from the implementation viewpoints
Let Your CyberAlter Ego Share Information and Manage Spam
Almost all of us have multiple cyberspace identities, and these {\em
cyber}alter egos are networked together to form a vast cyberspace social
network. This network is distinct from the world-wide-web (WWW), which is being
queried and mined to the tune of billions of dollars everyday, and until
recently, has gone largely unexplored. Empirically, the cyberspace social
networks have been found to possess many of the same complex features that
characterize its real counterparts, including scale-free degree distributions,
low diameter, and extensive connectivity. We show that these topological
features make the latent networks particularly suitable for explorations and
management via local-only messaging protocols. {\em Cyber}alter egos can
communicate via their direct links (i.e., using only their own address books)
and set up a highly decentralized and scalable message passing network that can
allow large-scale sharing of information and data. As one particular example of
such collaborative systems, we provide a design of a spam filtering system, and
our large-scale simulations show that the system achieves a spam detection rate
close to 100%, while the false positive rate is kept around zero. This system
has several advantages over other recent proposals (i) It uses an already
existing network, created by the same social dynamics that govern our daily
lives, and no dedicated peer-to-peer (P2P) systems or centralized server-based
systems need be constructed; (ii) It utilizes a percolation search algorithm
that makes the query-generated traffic scalable; (iii) The network has a built
in trust system (just as in social networks) that can be used to thwart
malicious attacks; iv) It can be implemented right now as a plugin to popular
email programs, such as MS Outlook, Eudora, and Sendmail.Comment: 13 pages, 10 figure
A Distributed Method for Trust-Aware Recommendation in Social Networks
This paper contains the details of a distributed trust-aware recommendation
system. Trust-base recommenders have received a lot of attention recently. The
main aim of trust-based recommendation is to deal the problems in traditional
Collaborative Filtering recommenders. These problems include cold start users,
vulnerability to attacks, etc.. Our proposed method is a distributed approach
and can be easily deployed on social networks or real life networks such as
sensor networks or peer to peer networks
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