LEWIS@cs.umass.EDU (11/04/88)
Can anyone point me to some references on matching of subparts of
frame-based knowledge representation structures? Essentially what I'm
interested in is equivalent to finding some/all/the biggest of the
isomorphic subgraphs of two directed graphs, except that edges and vertices
are labeled, and there are restrictions on what labels are allowed to match.
For additional fun, there might be weights on the edges and vertices as
well, and you might not just be interested in large-sized isomorphic
subgraphs, but in maximal scoring ones.
Still more interesting would be if anything has been done on the case where
you can inferences to the structures before matching, so that you actually
have to search a space of alternative representations, as well as comparing
them.
Suggestions? If text content matching had been a bigger application of NLP
in the past, there'd be a bunch of stuff on this, but as it is, I suspect that
vision or case based reasoning people may have done more on this.
Best,
David D. Lewis ph. 413-545-0728
Computer and Information Science (COINS) Dept. BITNET: lewis@umass
University of Massachusetts, Amherst ARPA/MIL/CS/INTERnet:
Amherst, MA 01003 lewis@cs.umass.edu
USA
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