Exploring Graph Representation of Chorales
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Abstract (arXiv)
This work explores areas overlapping music, graph theory, and machine learning. An embedding representation of a node, in a weighted undirected graph G, is a representation that captures the meaning of nodes in an embedding space. In this work, 383 Bach chorales were compiled and represented as a graph. Two application cases were investigated in this paper (i) learning node embedding representation using Continuous Bag of Words (CBOW), skip-gram, and node2vec algorithms, and (ii) learning node labels from neighboring nodes based on a collective classification approach. The results of this exploratory study ascertains many salient features of the graph-based representation approach applicable to music applications.
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References · 3
- 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,375
- 2016node2vec: Scalable Feature Learning for Networkscited by 1,918
- 2014word2vec Explained: deriving Mikolov et al.'s negative-sampling word-embedding methodcited by 112
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