  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.
