A scalable Peer-to-Peer System for Music Content and Information Retrieval

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Johns Hopkins University
Currently a large percentage of internet traffice consists of music files, typically stored in MP3 compressed audio format, shared and exchanged over Peer-to-Peer (P2P) networks. Searching for music is performed by specifying keywords and naive string matching techniques. In the past years the emerging research area of Music Information Retrieval (MIR) has produced a variety of new ways of looking at the problem of music search. Such MIR techniques can significantly enhance the ways users search for music over P2P networks. In order for that to happen there are two main challenges that need to be addressed: 1) scalability to large collections and number of peers 2) richer set of search semantics that can support MIR especially when retrieval is content-based. In this paper, we describe a scalable P2P system that uses Rendezvouz Points (RPs) for music metadata registration and query resolution, that supports atribute-value search semantics as well as content-based retrieval. The performance of the system has been evaluated in large scale usage scenarios using "real" automatically calculated musical content descriptors.
IR Systems and Algorithms, Digital Libraries