Adaptation for the masses:towards decentralised adaptation in large-scale P2P recommenders

Frey, Davide and Kermarrec, Anne-Marie and Maddock, Christopher and Mauthe, Andreas and Taïani, Francois (2014) Adaptation for the masses:towards decentralised adaptation in large-scale P2P recommenders. In: ARM '14 Proceedings of 13th Workshop on Adaptive and Reflective Middleware. ACM, New York. ISBN 9781450332323

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Decentralized recommenders have been proposed to deliver privacy-preserving, personalized and highly scalable on-line recommendation services. Current implementations tend, however, to rely on hard-wired, mechanisms that cannot adapt. Deciding beforehand which hard-wired mechanism to use can be difficult, as the optimal choice might depend on conditions that are unknown at design time. In this paper, propose a framework to develop dynamically adaptive decentralized recommendation systems. Our proposal supports a decentralized 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 services.

Item Type: Contribution in Book/Report/Proceedings
Departments: Faculty of Science and Technology > School of Computing & Communications
ID Code: 72750
Deposited By: ep_importer_pure
Deposited On: 30 Jan 2015 11:32
Refereed?: Yes
Published?: Published
Last Modified: 01 Jan 2020 05:49

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