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What is semi-supervised learning on graphs? We have been told that if we just have a function which has an input graph, or a given graph with labeled nodes, we should be able to predict labels on other nodes of the graph. This is not clear.

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    $\begingroup$ Why the down votes? The question may not be formulated properly, but there's substance in it? $\endgroup$ – Kris Jan 6 '12 at 6:22
  • $\begingroup$ yes it was not clear. were you told in a class by an instructor? it seems to be a general case of semi supervised learning, applied to labels on graphs. $\endgroup$ – vzn Mar 27 '14 at 15:01
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Semi-supervised learning means that you get both labelled and unlabelled data as your input. The graph part means that there is also a relation defined for your datapoints. What exactly it is that you learn and how you use the graph structure depends on the problem. Here is a thorough exploration of the subject: http://www.cs.cmu.edu/~zhuxj/pub/thesis.pdf

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