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Publication Citation: Extracting Hierarchies With Overlapping Structure From Network Data

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Author(s): Brian D. Cloteaux;
Title: Extracting Hierarchies With Overlapping Structure From Network Data
Published: December 11, 2011
Abstract: Relationships between entities in many complex systems, such as the Internet and social networks, have a natural hierarchical organization. Understanding these inherent hierarchies is essential for creating models of these systems. Thus, there is a recent body of research concerning the extraction of hierarchies from networks. We propose a new method for modeling hierarchies through extracting the affiliations of the network. From these affiliations, we construct a lattice of the relationships between nodes. A principal advantage of our approach is that any overlapping community structures of the nodes within the network have a natural representation within the lattice. We then show an example of our method using a real data set.
Proceedings: Winter Simulation Conference 2011
Pages: pp. 3335 - 3343
Location: Phoenix, AZ
Dates: December 11-14, 2011
Keywords: complex networks; hierarchy detection
Research Areas: Data Mining
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