Self-Organizing Maps
Content-based organization and visualization of music archives
Proceedings of the tenth ACM international conference on Multimedia
Using Smoothed Data Histograms for Cluster Visualization in Self-Organizing Maps
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
The Growing Hierarchical Self-Organizing Map
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 6 - Volume 6
Exploring Music Collections by Browsing Different Views
Computer Music Journal
An innovative three-dimensional user interface for exploring music collections enriched
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
IEEE Transactions on Computers
One-touch access to music on mobile devices
Proceedings of the 6th international conference on Mobile and ubiquitous multimedia
Multimedia Retrieval Algorithmics
SOFSEM '07 Proceedings of the 33rd conference on Current Trends in Theory and Practice of Computer Science
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
“Reinventing the Wheel”: A Novel Approach to Music Player Interfaces
IEEE Transactions on Multimedia
The CoMIRVA toolkit for visualizing music-related data
EUROVIS'07 Proceedings of the 9th Joint Eurographics / IEEE VGTC conference on Visualization
nepDroid: an intelligent mobile music player
Proceedings of the 2nd ACM International Conference on Multimedia Retrieval
Proceedings of the 9th International Symposium on Open Collaboration
Multimedia information retrieval: music and audio
Proceedings of the 21st ACM international conference on Multimedia
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We present a novel user interface that offers a fun way to explore music collections in virtual landscapes in a game-like manner. Extending previous work, special attention is paid to scalability and user interaction. In this vein, the ever growing size of today's music collections is addressed in two ways that allow for visualizing and browsing nearly arbitrarily sized music repositories. First, the proposed user interface deepTune employs a hierarchical version of the Self-Organizing Map (SOM) to cluster similar pieces of music using multiple, hierarchically aligned layers. Second, to facilitate orientation in the landscape by presenting well-known anchor points to the user, a combination of Web-based and audio signal-based information extraction techniques to determine cluster prototypes (songs) is proposed. Selecting representative and well-known prototypes -- the former is ensured by using signal-based features, the latter by using Web-based data -- is crucial for browsing large music collections. We further report on results of an evaluation carried out to assess the quality of the proposed cluster prototype ranking.