DocumentCode
2958378
Title
Enhancing SOM digital music archives using Scatter-Gather
Author
Azcarraga, Arnulfo P. ; Caw, Aldrirch C.
Author_Institution
De La Salle Univ., Manila
fYear
2008
fDate
1-8 June 2008
Firstpage
1833
Lastpage
1839
Abstract
The MarB system is a digital archive of music files that are clustered and laid out as a self-organized map, following the SOM methodology for large digital archives. The system has the usual music archive features as follows: 1) automatic clustering and organization of music files into ldquoislands of related musicrdquo; 2) classification of music clusters into various music genres; 3) playback of music files selected by the user; and 4) automatic generation of related music files for every music file that is chosen. In addition to these rather common features found in most self-organizing maps (SOM) based digital music archives, MarB also allows for an interactive selection and clustering of sets and subsets of music files until a specific music file is found. This is done using a Scatter/Gather interface that allows the user to select interesting clusters of music files (gather mode), which are then re-organized and re-clustered (scatter mode) for the user to visually inspect and possibly listen to. The user is then asked to select new interesting clusters (gather mode again). This alternating selection and re-clustering process continues until the user chooses a specific music file, and is provided with a set of most related music files. A novel album dispersal measure is used to objectively assess the quality of the clusters produced both by the SOM and the special k -means algorithm employed in the Scatter-Gather module.
Keywords
file organisation; information retrieval systems; music; self-organising feature maps; SOM digital music archives; Scatter-Gather module; automatic clustering; automatic generation; music files organization; self-organized map; Neural networks; Scattering;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location
Hong Kong
ISSN
1098-7576
Print_ISBN
978-1-4244-1820-6
Electronic_ISBN
1098-7576
Type
conf
DOI
10.1109/IJCNN.2008.4634047
Filename
4634047
Link To Document