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Erschienen in:
2009 | OriginalPaper | Buchkapitel
Graph-Based Representation of Symbolic Musical Data
verfasst von : Bassam Mokbel, Alexander Hasenfuss, Barbara Hammer
Erschienen in: Graph-Based Representations in Pattern Recognition
Verlag: Springer Berlin Heidelberg
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In this work, we present an approach that utilizes a graph-based representation of symbolic musical data in the context of automatic topographic mapping. A novel approach is introduced that represents melodic progressions as graph structures providing a dissimilarity measure which complies with the invariances in the human perception of melodies. That way, music collections can be processed by non-Euclidean variants of Neural Gas or Self-Organizing Maps for clustering, classification, or topographic mapping for visualization. We demonstrate the performance of the technique on several datasets of classical music.