Download PDFOpen PDF in browserExploring Graph Representation of ChoralesEasyChair Preprint 887215 pages•Date: September 24, 2022AbstractThis work explores uncharted 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 representation. 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 ascertain many salient features of the graph-based representation approach. Keyphrases: Node embedding representation, collective classification, graph representation learning, node2vec
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