Spectral clustering of annotated graphs using a factor graph representation
arXiv:2010.02791
Abstract
Graph-structured data commonly have node annotations. A popular approach for inference and learning involving annotated graphs is to incorporate annotations into a statistical model or algorithm. By contrast, we consider a more direct method named scotch-taping, in which the structural information in a graph and its node annotations are encoded as a factor graph. Specifically, we establish the mathematical basis of this method in the spectral framework.
24 pages, 8 figures
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