Modeling Bipartite Graphs Using Hierarchical Structures
Conference Proceeding Article
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.
bipartite graphs, bipartite networks, disassortative structures, hierarchical random graph model, network fidelity, optimal bipartite hierarchical structure
Databases and Information Systems | Numerical Analysis and Scientific Computing
Data Management and Analytics
International Conference on Advances in Social Network Analysis and Mining (ASONAM2011)
City or Country
Kaohsiung, Taiwan, July 2011
CHUA, Freddy Chong-Tat and LIM, Ee Peng.
Modeling Bipartite Graphs Using Hierarchical Structures. (2011). International Conference on Advances in Social Network Analysis and Mining (ASONAM2011). Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/1438