Title :
Extracting hierarchies with overlapping structure from network data
Author_Institution :
Math. & Comput. Sci. Div., Nat. Inst. of Stand. & Technol., Gaithersburg, MD, USA
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.
Keywords :
information networks; network theory (graphs); affiliation networks; hierarchical organization; hierarchy extraction; network data; overlapping community structures; relationship attice; Biological system modeling; Computational modeling; Context; Data mining; Lattices; Organizations; Standards organizations;
Conference_Titel :
Simulation Conference (WSC), Proceedings of the 2011 Winter
Conference_Location :
Phoenix, AZ
Print_ISBN :
978-1-4577-2108-3
Electronic_ISBN :
0891-7736
DOI :
10.1109/WSC.2011.6148029