Name
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. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1145/1739041.1739055 | Extending Database Technology |
Keywords | Field | DocType |
top-k query processing,decentralized gossip-based protocol,bandwidth consumption,social acquaintance,experimental evaluation,000-user delicious trace,similar tagging behaviour,p3q dynamically associate,social tagging system,query processing,personalized query,region | Query optimization,Data mining,Query language,Computer science,On the fly,Web query classification,Gossip,Bandwidth (signal processing),Database,Scalability | Conference |
Citations | PageRank | References |
14 | 0.56 | 26 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiao Bai | 1 | 15 | 1.59 |
| Marin Bertier | 2 | 382 | 24.31 |
| Rachid Guerraoui | 3 | 6364 | 430.90 |
| Anne-Marie Kermarrec | 4 | 6649 | 453.63 |
| Vincent Leroy | 5 | 197 | 18.23 |