Similitude : decentralised adaptation in large-scale P2P recommenders

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 : 15th IFIP WG 6.1 International Conference, DAIS 2015, Held as Part of the 10th International Federated Conference on Distributed Computing Techniques, DisCoTec 2015, Grenoble, France, June 2-4, 2015, Pr. Lecture Notes in Computer Science . Springer, pp. 51-65. ISBN 9783319191287

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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

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28 Jan 2016 13:20
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21 Apr 2024 23:29