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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Vydáno v:	Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01 Ročník 1; s. 242 - 248
Hlavní autoři:	Goussevskaia, Olga, Kuhn, Michael, Lorenzi, Michael, Wattenhofer, Roger
Médium:	Konferenční příspěvek
Jazyk:	angličtina
Vydáno:	Washington, DC, USA IEEE Computer Society 09.12.2008 IEEE
Edice:	ACM Conferences
Témata:	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
On-line přístup:	Získat plný text
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Popis
Shrnutí:	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