Collaborative personalized top-k processing

  • Authors:
  • Xiao Bai;Rachid Guerraoui;Anne-Marie Kermarrec;Vincent Leroy

  • Affiliations:
  • Yahoo! Research Barcelona, Spain;EPFL, Switzerland;INRIA Rennes Bretagne-Atlantique, France;Yahoo! Research Barcelona, Spain

  • Venue:
  • ACM Transactions on Database Systems (TODS)
  • Year:
  • 2011

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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.