Frey, David and Kermarrec, Anne-Marie and Maddock, Christopher and Mauthe, Andreas Ulrich and Roman, Pierre-Louis and Taiani, Francois (2015) Similitude:decentralised adaptation in large-scale P2P recommenders. In: Distributed Applications and Interoperable Systems. Lecture Notes in Computer Science . Springer, pp. 51-65. ISBN 9783319191287
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Abstract
Decentralised recommenders have been proposed to deliver privacy-preserving, personalised and highly scalable on-line recommendations. Current implementations tend, however, to rely on a hard-wired similarity metric that cannot adapt. This constitutes a strong limitation in the face of evolving needs. In this paper, we propose a framework to develop dynamically adaptive decentralised recommendation systems. Our proposal supports a decentralised form of adaptation, in which individual nodes can independently select, and update their own recommendation algorithm, while still collectively contributing to the overall system’s mission. Keywords