Carretero, Jesus and Isaila, Florin and Kermarrec, Anne-Marie and Taïani, Francois and Tirado, Juan M (2012) Geology: Modular Georecommendation In Gossip-Based Social Networks. In: Proceedings of the IEEE 32nd International Conference on Distributed Computing Systems (ICDCS 2012). IEEE, pp. 637-646. ISBN 978-1-4577-0295-2Full text not available from this repository.
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.
|Item Type:||Contribution in Book/Report/Proceedings|
|Uncontrolled Keywords:||distributed systems ; geolocation ; gossip protocols ; social networks|
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science|
|Departments:||Faculty of Science and Technology > School of Computing & Communications|
|Deposited On:||20 Aug 2012 11:18|
|Last Modified:||29 Apr 2017 03:37|
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