Collaborative Personalized Top-k Processing

This article presents P4Q, a fully decentralized gossip-based protocol to personalize query processing in social tagging systems. P4Q dynamically associates each user with social acquaintances sharing similar tagging behaviors. 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 P4Q for top-k query processing, as well its inherent ability to cope with users updating profiles and departing.


Published in:
ACM Transactions on Database Systems, 36, -
Year:
2011
Publisher:
Association for Computing Machinery
ISSN:
0362-5915
Keywords:
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 Record created 2012-06-25, last modified 2018-12-03

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