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Geology: Modular Georecommendation In Gossip-Based Social Networks

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Geology: Modular Georecommendation In Gossip-Based Social Networks. / Carretero, Jesus; Isaila, Florin; Kermarrec, Anne-Marie et al.
Proceedings of the IEEE 32nd International Conference on Distributed Computing Systems (ICDCS 2012). IEEE, 2012. p. 637-646.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Carretero, J, Isaila, F, Kermarrec, A-M, Taïani, F & Tirado, JM 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. https://doi.org/10.1109/ICDCS.2012.36

APA

Carretero, J., Isaila, F., Kermarrec, A-M., Taïani, F., & Tirado, J. M. (2012). Geology: Modular Georecommendation In Gossip-Based Social Networks. In Proceedings of the IEEE 32nd International Conference on Distributed Computing Systems (ICDCS 2012) (pp. 637-646). IEEE. https://doi.org/10.1109/ICDCS.2012.36

Vancouver

Carretero J, Isaila F, Kermarrec A-M, Taïani F, Tirado JM. Geology: Modular Georecommendation In Gossip-Based Social Networks. In Proceedings of the IEEE 32nd International Conference on Distributed Computing Systems (ICDCS 2012). IEEE. 2012. p. 637-646 doi: 10.1109/ICDCS.2012.36

Author

Carretero, Jesus ; Isaila, Florin ; Kermarrec, Anne-Marie et al. / Geology: Modular Georecommendation In Gossip-Based Social Networks. Proceedings of the IEEE 32nd International Conference on Distributed Computing Systems (ICDCS 2012). IEEE, 2012. pp. 637-646

Bibtex

@inproceedings{160198dea89e47f1bf5bfece7aa470b1,
title = "Geology: Modular Georecommendation In Gossip-Based Social Networks",
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.",
keywords = "distributed systems , geolocation , gossip protocols , social networks",
author = "Jesus Carretero and Florin Isaila and Anne-Marie Kermarrec and Francois Ta{\"i}ani and Tirado, {Juan M}",
year = "2012",
month = jun,
doi = "10.1109/ICDCS.2012.36",
language = "English",
isbn = "978-1-4577-0295-2",
pages = "637--646",
booktitle = "Proceedings of the IEEE 32nd International Conference on Distributed Computing Systems (ICDCS 2012)",
publisher = "IEEE",

}

RIS

TY - GEN

T1 - Geology: Modular Georecommendation In Gossip-Based Social Networks

AU - Carretero, Jesus

AU - Isaila, Florin

AU - Kermarrec, Anne-Marie

AU - Taïani, Francois

AU - Tirado, Juan M

PY - 2012/6

Y1 - 2012/6

N2 - 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.

AB - 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.

KW - distributed systems

KW - geolocation

KW - gossip protocols

KW - social networks

U2 - 10.1109/ICDCS.2012.36

DO - 10.1109/ICDCS.2012.36

M3 - Conference contribution/Paper

SN - 978-1-4577-0295-2

SP - 637

EP - 646

BT - Proceedings of the IEEE 32nd International Conference on Distributed Computing Systems (ICDCS 2012)

PB - IEEE

ER -