| 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 |
| PDF version: |
 Click here to retrieve PDF version of paper (525KB) |
