Date Added: Jun 2010
Peer-To-Peer (p2p) networks are being increasingly adopted as an invaluable resource for various Music Information Retrieval (MIR) tasks, including music similarity, recommendation and trend prediction. However, these networks are usually extremely large and noisy, which raises doubts regarding the ability to actually extract sufficiently accurate information. This paper evaluates the applicability of using data originating from p2p networks for MIR research, focusing on partial crawling, inherent noise and localization of songs and search queries. These aspects are quantified using songs collected from the Gnutella p2p network.