Hello,
I am starting learning about graph theory and as I am a Python practitioner, I
decided to start looking what is available in Python. Among all the choices I
could find, igraph seems to be a great tool. Thus I have decided to know
further about it. Currently I am trying to solve a problem by graph matching. I
know there is several ways to process graph matching, but in my problem my
approach is as follow. Given a graph source and a graph target, having both
their nodes labeled with some attributes, I compute a similarity function for
"two close" nodes, based in the attributes associated to the nodes.
Iteratively, I start with a node in the "graph source", for this node I want
to find all close "nodes in target graph" . Two nodes are close if the
similarity function score is greater than a threshold. When a close node is
found I want to create another graph (a tree) having the source node pointing
toward the close node. The similarity score is then set as weight in the edges
of the new graph.
Conceptually, the idea is simple, but in practice I don't know how I can
iterate over the nodes, and how I can create the second weighted graph using
igraph.
I really appreciate if some one could give me some help to solve this problem.
thanks in advance.
Best regards,
Ilisio
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