Hi, A common trick is to construct the line graph of the original graph, do the clustering on the line graph (where each node corresponds to a single edge from the original graph), and then map the obtained clustering back to the edges of the original graph.
T. On Fri, May 26, 2017 at 10:53 PM, lookman sanni <[email protected]> wrote: > Hi all, > > I am currently investigating graph clustering techniques/algorithms for > the purpose of anomaly detection in static, edge attributed and > disconnected graphs. > > From what I have seen so far, most of the graph clustering algorithms for > anomaly detection output either a binary *node *classification or a *node > *anomaly score. > > To the best of your knowledge, is there any algorithm rather providing > either a binary *edge* classification or an *edge* anomaly score ? > > Thank you. > > > -- > > Lookman SANNI > > _______________________________________________ > igraph-help mailing list > [email protected] > https://lists.nongnu.org/mailman/listinfo/igraph-help > >
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