Enhancing SOM digital music archives using scatter-gather
College
College of Computer Studies
Department/Unit
Computer Technology
Document Type
Conference Proceeding
Source Title
Proceedings of the International Joint Conference on Neural Networks
First Page
1833
Last Page
1839
Publication Date
11-24-2008
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 "islands of related music"; 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 flies 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 flies 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. © 2008 IEEE.
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Digitial Object Identifier (DOI)
10.1109/IJCNN.2008.4634047
Recommended Citation
Azcarraga, A. P., & Caw, A. C. (2008). Enhancing SOM digital music archives using scatter-gather. Proceedings of the International Joint Conference on Neural Networks, 1833-1839. https://doi.org/10.1109/IJCNN.2008.4634047
Disciplines
Computer Sciences
Keywords
Self-organizing maps; Document clustering; File organization (Computer science)
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