Adaptation for the Masses: Towards Decentralized Adaptation in Large-Scale P2P RecommendersReport as inadecuate




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1 ASAP - As Scalable As Possible: foundations of large scale dynamic distributed systems Inria Rennes – Bretagne Atlantique , IRISA-D1 - SYSTÈMES LARGE ÉCHELLE 2 Computing Department

Abstract : 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 pa-per, propose a framework to develop dynamically adaptive decentralized recommendation systems. Our proposal sup-ports a decentralized form of adaptation, in which individual nodes can independently select, and update their own rec-ommendation algorithm, while still collectively contributing to the overall system-s services.

Keywords : Collaborative filtering Recommendation systems Hetero-geneity Adaptivity





Author: Davide Frey - Anne-Marie Kermarrec - Christopher Maddock - Andreas Mauthe - François Taïani -

Source: https://hal.archives-ouvertes.fr/



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