Multi-Layer Graph Analysis for Dynamic Social Networks

作者：Oselio Brandon^*; Kulesza Alex; Hero Alfred O III

来源：IEEE Journal of Selected Topics in Signal Processing, 2014, 8(4): 514-523.

DOI：10.1109/JSTSP.2014.2328312

• Hypergraphs
• mixture graphical models
• multi-graphs
• Pareto optimality

Modern social networks frequently encompass multiple distinct types of connectivity information; for instance, explicitly acknowledged friend relationships might complement behavioral measures that link users according to their actions or interests. One way to represent these networks is as multi-layer graphs, where each layer contains a unique set of edges over the same underlying vertices (users). Edges in different layers typically have related but distinct semantics; depending on the application multiple layers might be used to reduce noise through averaging, to perform multifaceted analyses, or a combination of the two. However, it is not obvious how to extend standard graph analysis techniques to the multi-layer setting in a flexible way. In this paper we develop latent variable models and methods for mining multi-layer networks for connectivity patterns based on noisy data.

• 出版日期2014-8