Collaborative filtering based on P2P networks

Noam Koenigstein, Gert Lanckriet, Brian McFee, Yuval Shavitt

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

Abstract

Peer-to-Peer (P2P) networks are used by millions of people for sharing music files. As these networks become ever more popular, they also serve as an excellent source for Music Information Retrieval (MIR) tasks. This paper reviews the latest MIR studies based on P2P data-sets, and presents a new file sharing data collection system over the Gnutella. We discuss several advantages of P2P based data-sets over some of the more "traditional" data sources, and evaluate the information quality of our data-set in comparison to other data sources (Last.fm, social tags, biography data, and MFCCs). The evaluation is based on an artists similarity task using Partial Order Embedding (POE). We show that a P2P based Collaborative Filtering dataset performs at least as well as "traditional" data-sets, yet maintains some inherent advantages such as scale, availability and additional information features such as ID3 tags and geographical location.

Original languageEnglish
Title of host publicationProceedings of the 11th International Society for Music Information Retrieval Conference, ISMIR 2010
Pages153-158
Number of pages6
StatePublished - 2010
Event11th International Society for Music Information Retrieval Conference, ISMIR 2010 - Utrecht, Netherlands
Duration: 9 Aug 201013 Aug 2010

Publication series

NameProceedings of the 11th International Society for Music Information Retrieval Conference, ISMIR 2010

Conference

Conference11th International Society for Music Information Retrieval Conference, ISMIR 2010
Country/TerritoryNetherlands
CityUtrecht
Period9/08/1013/08/10

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