This paper presents P3Q, a fully decentralized gossip-based proto-col to personalize query processing in social tagging systems. P3Q dynamically associates each user with social acquaintances shar-ing similar tagging behaviours. Queries are gossiped among such acquaintances, computed on the fly in a collaborative, yet parti-tioned 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. 1.
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Bai et al. (2010) studied this question.
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