Applying clustering algorithms on peer-to-peer networks for content searching and recommendation

Yuval Shavitt*, Ela Weinsberg, Udi Weinsberg

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Peer-to-Peer (p2p) networks are used by millions for searching content. Recently, clustering algorithms were shown to be useful for helping users find content in such networks. However, p2p networks often exhibit power-law node degree distribution, causing biased results when clustered using current algorithms. In order to overcome this bias, an efficient clustering algorithm is presented, which targets a relaxed optimization of a minimal distance distribution of each cluster with an additional size balancing scheme. Using song similarity graph collected from crawling 1.2 millions users in the Gnutella p2p network, we present methods for improving the ability to search for content and build novel recommendation systems.

Original languageEnglish
Title of host publication2010 IEEE 26th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2010
Pages244-248
Number of pages5
DOIs
StatePublished - 2010
Event2010 IEEE 26th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2010 - Eilat, Israel
Duration: 17 Nov 201020 Nov 2010

Publication series

Name2010 IEEE 26th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2010

Conference

Conference2010 IEEE 26th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2010
Country/TerritoryIsrael
CityEilat
Period17/11/1020/11/10

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