Toward personalized peer-to-peer top-k processing

Authors:
Xiao Bai;Marin Bertier;Rachid Guerraoui;Anne-Marie Kermarrec
Affiliations:
INSA de Rennes, France;INSA de Rennes, France;EPFL, Switzerland;INRIA Rennes, France
Venue:
Proceedings of the Second ACM EuroSys Workshop on Social Network Systems
Year:
2009

Citing 6
Cited 3

Combining fuzzy information: an overview

ACM SIGMOD Record
PlanetP: Using Gossiping to Build Content Addressable Peer-to-Peer Information Sharing Communities

HPDC '03 Proceedings of the 12th IEEE International Symposium on High Performance Distributed Computing
KLEE: a framework for distributed top-k query algorithms

VLDB '05 Proceedings of the 31st international conference on Very large data bases
Gossip-based peer sampling

ACM Transactions on Computer Systems (TOCS)
Exploring folksonomy for personalized search

Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Efficient top-k querying over social-tagging networks

Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval

Challenges in Personalizing and Decentralizing the Web: An Overview of GOSSPLE

SSS '09 Proceedings of the 11th International Symposium on Stabilization, Safety, and Security of Distributed Systems
Gossiping personalized queries

Proceedings of the 13th International Conference on Extending Database Technology
Collaborative personalized top-k processing

ACM Transactions on Database Systems (TODS)

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present the first personalized peer-to-peer top-k search protocol for a collaborative tagging system. Each peer maintains relevant personalized information about its tagging behavior as well as that of its social neighbors, and uses those to locally process its queries. Extensive experiments based on a real-world dataset crawled from del.icio.us shows that very little storage at each peer suffices to get almost the same results as a hypothetical centralized solution with infinite storage.