From Web to Map Exploring the World of Music

Ever growing music collections ask for novel ways of organization. The traditional browsing of folder hierarchies or search by title and album tends to be insufficient to maintain an overview of a collection of orders of thousands of tracks. Methods based on song similarity offer an alternative to k...

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Bibliographic Details
Published in:Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01 Vol. 1; pp. 242 - 248
Main Authors: Goussevskaia, Olga, Kuhn, Michael, Lorenzi, Michael, Wattenhofer, Roger
Format: Conference Proceeding
Language:English
Published: Washington, DC, USA IEEE Computer Society 09.12.2008
IEEE
Series:ACM Conferences
Subjects:
Applied computing > Arts and humanities > Performing arts
Applied computing > Arts and humanities > Sound and music computing
Collaboration
collaborative filtering
Concrete
Data structures
embedding
graph
high-dimensional space
Information analysis
Information filtering
Information filters
Information systems > Information retrieval
Information systems > Information retrieval > Specialized information retrieval > Multimedia and multimodal retrieval > Music retrieval
Information systems > Information storage systems
Intelligent agent
music
Music information retrieval
music similarity
Navigation
playlist
Visualization
collaborative filtering
visualization
music
playlist
embedding
graph
high-dimensional space
music similarity
ISBN:9780769534961, 0769534961
Online Access:Get full text
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Summary:Ever growing music collections ask for novel ways of organization. The traditional browsing of folder hierarchies or search by title and album tends to be insufficient to maintain an overview of a collection of orders of thousands of tracks. Methods based on song similarity offer an alternative to keyword-based search. In this work we propose to use a high-dimensional map of the "world of music" as a data structure for music retrieval and exploration of personal collections. Our approach does not require expensive analysis of audio signals and scales to hundreds of thousands of tracks. The techniques presented in this work can be used in a variety of applications, ranging from automatic DJs to file sharing on mobile devices. As a concrete example, we have developed a web-application that allows users to visualize and navigate through their music collections and create playlists by specifying trajectories.
ISBN:9780769534961
0769534961
DOI:10.1109/WIIAT.2008.20