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2012 IEEE 32nd International Conference on Distributed Computing Systems (2012)
Macau, China China
June 18, 2012 to June 21, 2012
ISSN: 1063-6927
ISBN: 978-1-4577-0295-2
pp: 637-646
ABSTRACT
Geolocated social networks, combining traditional social networking features with geolocation information, have grown tremendously over the last few years. Yet, very few works have looked at implementing geolocated social networks in a fully distributed manner, a promising avenue to handle the growing scalability challenges of these systems. In this paper, we focus on georecommendation, and show that existing decentralized recommendation mechanisms perform in fact poorly on geodata. We propose a set of novel gossip-based mechanisms to address this problem, in a modular similarity framework called GEOLOGY. The resulting platform is lightweight, efficient, and scalable, and we demonstrate its advantages in terms of recommendation quality and communication overhead on a real dataset of 15,694 users from Foursquare, a leading geolocated social network.
INDEX TERMS
Geology, Measurement, Peer to peer computing, Compaction, Twitter, Vectors, gossip protocols, distributed systems, social networks, geolocation
CITATION

F. Taiani, A. Kermarrec, F. Isaila, J. Carretero and J. M. Tirado, "Geology: Modular Georecommendation in Gossip-Based Social Networks," 2012 IEEE 32nd International Conference on Distributed Computing Systems(ICDCS), Macau, China China, 2012, pp. 637-646.
doi:10.1109/ICDCS.2012.36
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