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Gossiping Personalized Queries

Abstract : This paper presents P3Q, a fully decentralized gossip-based protocol to personalize query processing in social tagging systems. P3Q dynamically associates each user with social acquaintances sharing similar tagging behaviours. Queries are gossiped among such acquaintances, computed on the fly in a collaborative, yet partitioned manner, and results are iteratively refined and returned to the querier. Analytical and experimental evaluations convey the scalability of P3Q for top-k query processing. More specifically, we show that on a 10,000-user delicious trace, with little storage at each user, the queries are accurately computed within reasonable time and bandwidth consumption. We also report on the inherent ability of P3Q to cope with users updating profiles and departing.
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https://hal.inria.fr/inria-00455643
Contributor : Xiao Bai <>
Submitted on : Wednesday, April 21, 2010 - 6:21:40 PM
Last modification on : Tuesday, June 15, 2021 - 4:27:55 PM
Long-term archiving on: : Thursday, June 30, 2011 - 12:08:16 PM

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  • HAL Id : inria-00455643, version 1

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Xiao Bai, Marin Bertier, Rachid Guerraoui, Anne-Marie Kermarrec, Vincent Leroy. Gossiping Personalized Queries. 13th International Conference on Extending Database Technology, Mar 2010, Lausanne, Switzerland. ⟨inria-00455643⟩

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