Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Content-based organization and visualization of music archives
Proceedings of the tenth ACM international conference on Multimedia
User Modelling for Interactive User-Adaptive Collection Structuring
Adaptive Multimedial Retrieval: Retrieval, User, and Semantics
Weighted self-organizing maps: incorporating user feedback
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Video navigation based on self-organizing maps
CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
CMMR'10 Proceedings of the 7th international conference on Exploring music contents
MusicGalaxy: a multi-focus zoomable interface for multi-facet exploration of music collections
CMMR'10 Proceedings of the 7th international conference on Exploring music contents
Music thumbnailing incorporating harmony- and rhythm structure
AMR'08 Proceedings of the 6th international conference on Adaptive Multimedia Retrieval: identifying, Summarizing, and Recommending Image and Music
Similarity adaptation in an exploratory retrieval scenario
AMR'10 Proceedings of the 8th international conference on Adaptive Multimedia Retrieval: context, exploration, and fusion
Bisociative music discovery and recommendation
Bisociative Knowledge Discovery
An experimental comparison of similarity adaptation approaches
AMR'11 Proceedings of the 9th international conference on Adaptive Multimedia Retrieval: large-scale multimedia retrieval and evaluation
Adaptive music retrieval---a state of the art
Multimedia Tools and Applications
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We present a prototype system for organization and exploration of music archives that adapts to the user’s way of structuring music collections. Initially, a growing self-organizing map is induced that clusters the music collection. The user has then the possibility to change the location of songs on the map by simple drag-and-drop actions. Each movement of a song causes a change in the underlying similarity measure based on a quadratic optimization scheme. As a result, the location of other songs is modified as well. Experiments simulating user interaction with the system show, that during this stepwise adaptation the similarity measure indeed converges to one that captures how the user compares songs. This utimately leads to an individually adapted presentation that is intuitively understandable to the user and thus eases access to the database.