Spectral clustering of annotated graphs using a factor graph representation
Social and Information Networks
2020-10-07 v1 Physics and Society
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.
Cite
@article{arxiv.2010.02791,
title = {Spectral clustering of annotated graphs using a factor graph representation},
author = {Tatsuro Kawamoto},
journal= {arXiv preprint arXiv:2010.02791},
year = {2020}
}
Comments
24 pages, 8 figures