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. 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

Item Type:
Contribution in Book/Report/Proceedings
Additional Information:
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-19129-4_5
ID Code:
78012
Deposited By:
Deposited On:
28 Jan 2016 13:20
Refereed?:
Yes
Published?:
Published
Last Modified:
02 Apr 2020 00:53