MobHinter: Epidemic collaborative filtering and self-organization in mobile ad-hoc networks

Rossano Schifanella, Andŕ Panisson, Cristina Gena, Giancarlo Ruffo

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Abstract

We focus on collaborative filtering dealing with self-organizing communities, host mobility, wireless access, and ad-hoc communications. In such a domain, knowledge representation and users profiling can be hard; remote servers can be often unreachable due to client mobility; and feedback ratings collected during random connections to other users' adhoc devices can be useless, because of natural differences between human beings. Our approach is based on so called Affinity Networks, and on a novel system, called MobHinter, that epidemically spreads recommendations through spontaneous similarities between users. Main results of our study are two fold: firstly, we show how to reach comparable recommendation accuracies in the mobile domain as well as in a complete knowledge scenario; secondly, we propose epidemic collaborative strategies that can reduce rapidly and realistically the cold start problem.

Lingua originaleInglese
Titolo della pubblicazione ospiteRecSys'08
Sottotitolo della pubblicazione ospiteProceedings of the 2008 ACM Conference on Recommender Systems
Pagine27-34
Numero di pagine8
DOI
Stato di pubblicazionePubblicato - 2008
Pubblicato esternamente
Evento2008 2nd ACM International Conference on Recommender Systems, RecSys'08 - Lausanne, Switzerland
Durata: 23 ott 200825 ott 2008

Serie di pubblicazioni

NomeRecSys'08: Proceedings of the 2008 ACM Conference on Recommender Systems

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???event.eventtypes.event.conference???2008 2nd ACM International Conference on Recommender Systems, RecSys'08
Paese/TerritorioSwitzerland
CittàLausanne
Periodo23/10/0825/10/08

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