Modeling bipartite graphs using hierarchical structures

Publication Type

Conference Proceeding Article

Publication Date

2011

Abstract

Bipartite networks are often used to capture the relationships between different classes of objects. To model the structure of bipartite networks, we propose a new hierarchical model based on a hierarchical random graph model originally designed for one-mode networks. The new model can better preserve the network fidelity as well as the assortative and disassortative structures of bipartite networks. We apply the proposed model on some paper-author networks in DBLP to find their optimal hierarchical structures. Using the optimal bipartite hierarchical structure, we regenerate networks that exhibit the similar network properties and degree distribution as the observed networks.

Keywords

Bipartite graphs, Bipartite networks, Disassortative structures, Hierarchical random graph model, Network fidelity, Optimal Bipartite hierarchical structure

Discipline

Databases and Information Systems | Numerical Analysis and Scientific Computing

Publication

International Conference on Advances in Social Network Analysis and Mining (ASONAM2011)

Identifier

10.1109/ASONAM.2011.45

Publisher

IEEE

City or Country

Kaohsiung, Taiwan, July 2011

Additional URL

http://doi.org/10.1109/ASONAM.2011.45

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