TY - GEN
T1 - A framework for extracting musical similarities from peer-to-peer networks
AU - Koenigstein, Noam
AU - Shavitt, Yuval
AU - Tankel, Tomer
AU - Weinsberg, Ela
AU - Weinsberg, Udi
N1 - Funding Information:
This work was supported by project the FCT (ISR/IST plurianual funding) through the PIDDAC Program funds, partially funded with grant SFRH/BD/48526/2008, from Fun-dao para a Ciłncia e a Tecnologia, and by the project CMU-PT/SIA/0023/2009 under the Carnegie Mellon-Portugal Program.
PY - 2010
Y1 - 2010
N2 - The usage of peer-to-peer (p2p) networks for music information retrieval (MIR) tasks is gaining momentum. P2P file sharing networks can be used for collecting both search queries and files from shared folders. The first can be utilized to reveal current taste, users interest, and trends, while the latter can be used for enhancing recommender systems. Both provide opportunities for longitudinal analysis, as queries change over time and content often accumulates. Moreover, spatial analysis can expose cultural differences and the way trends propagate. However, tapping into this fountain of information is far from trivial. This paper presents a novel analysis of the shared folders data-set collected from the Gnutella network. We first present the framework for crawling the network and collecting the data. We then present some data-set characteristics, while focusing on music similarities. The paper sheds light on both the opportunities of using p2p data and its complexities.
AB - The usage of peer-to-peer (p2p) networks for music information retrieval (MIR) tasks is gaining momentum. P2P file sharing networks can be used for collecting both search queries and files from shared folders. The first can be utilized to reveal current taste, users interest, and trends, while the latter can be used for enhancing recommender systems. Both provide opportunities for longitudinal analysis, as queries change over time and content often accumulates. Moreover, spatial analysis can expose cultural differences and the way trends propagate. However, tapping into this fountain of information is far from trivial. This paper presents a novel analysis of the shared folders data-set collected from the Gnutella network. We first present the framework for crawling the network and collecting the data. We then present some data-set characteristics, while focusing on music similarities. The paper sheds light on both the opportunities of using p2p data and its complexities.
KW - Data-mining
KW - File-sharing
KW - Information Retrieval
KW - Peer-to-peer
UR - http://www.scopus.com/inward/record.url?scp=78349241051&partnerID=8YFLogxK
U2 - 10.1109/ICME.2010.5583251
DO - 10.1109/ICME.2010.5583251
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AN - SCOPUS:78349241051
SN - 9781424474912
T3 - 2010 IEEE International Conference on Multimedia and Expo, ICME 2010
SP - 1433
EP - 1438
BT - 2010 IEEE International Conference on Multimedia and Expo, ICME 2010
PB - IEEE Computer Society
ER -