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2009

Community Detection with and without Prior Information

Allahverdyan, Armen E., Steeg, Greg Ver, Galstyan, Aram

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We study the problem of graph partitioning, or clustering, in sparse networks with prior information about the clusters.

Specifically, we assume that for a fraction $\rho$ of the nodes their true cluster assignments are known in advance.
This can be understood as a semi--supervised version of clustering, in contrast to unsupervised clustering where the only available information is the graph structure.
In the unsupervised case, it is known that there is a threshold of the inter--cluster connectivity beyond which clusters cannot be detected.

Community Detection with and without Prior Information · Around

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