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Collaborative Personalized Top-k Processing

Abstract : 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.
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Contributor : Anne-Marie Kermarrec Connect in order to contact the contributor
Submitted on : Wednesday, December 14, 2011 - 5:10:59 PM
Last modification on : Monday, April 4, 2022 - 3:28:09 PM

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Xiao Bai, Rachid Guerraoui, Anne-Marie Kermarrec, Vincent Leroy. Collaborative Personalized Top-k Processing. ACM Transactions on Database Systems, Association for Computing Machinery, 2011, 36 (4), ⟨10.1145/2043652.2043659⟩. ⟨hal-00652036⟩



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