Content-based retrieval of music in scalable peer-to-peer networks

被引：0

作者：

Gao, J ^{[1
]}

Tzanetakis, G ^{[1
]}

Steenkiste, P ^{[1
]}

机构：

[1] Carnegie Mellon Univ, Sch Comp Sci, Pittsburgh, PA 15213 USA

来源：

2003 INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO, VOL I, PROCEEDINGS | 2003年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A large portion of data exchanged in today's Peer-to-Peer (P2P) networks consists of music stored as MP3 compressed audio. Existing P2P systems typically are not scalable and only support primitive methods for the searching of music files, e.g., by looking up exact filenames or using simple metadata information such as artist or album name. In this paper, we present the design and evaluation of a scalable P2P system that uses Rendezvous Points (RPs) for music file registration and query resolution, and supports content-based Music Information Retrieval (MIR) of audio signals.

引用

页码：309 / 312

页数：4

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