Abstract
The categorization of vertices in a network is a common task across a multitude of domains. Specifically, identifying structural divisions into internally well connected sets have been shown to be useful in computer science, social science, and biology. In each of these areas, grouping vertices using structural boundaries helps one to understand the underlying processes of a network. Identifying such groupings is a non-trivial task and has been a subject of intense research in recent years.
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Acknowledgements
Research was sponsored by the Army Research Laboratory and was accomplished under Cooperative Agreement Number W911NF-09-2-0053 and by UT-Battelle, a contractor for the U.S. Government under Department of Energy Contract DE-AC05-00OR22725. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on.
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Kelley, S., Goldberg, M., Magdon-Ismail, M., Mertsalov, K., Wallace, A. (2012). Defining and Discovering Communities in Social Networks. In: Thai, M., Pardalos, P. (eds) Handbook of Optimization in Complex Networks. Springer Optimization and Its Applications(), vol 57. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-0754-6_6
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