NONPARAMETRIC BAYESIAN MATRIX FACTORIZATION FOR ASSORTATIVE NETWORKS

被引：0
|
作者：
Zhou, Mingyuan [1 ]
机构：
[1] Univ Texas Austin, McCombs Sch Business, IROM Dept, Austin, TX 78712 USA
来源：
2015 23RD EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO) | 2015年
关键词：
Gamma process; factor analysis; Bernoulli-Poisson link; overlapping conununity detection; link prediction;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
We describe in detail the gamma process edge partition model that is well suited to analyze assortative relational networks. The model links the binary edges of an undirected and unweighted relational network with a latent factor model via the Bernoulli-Poisson link, and uses the gamma process to support a potentially infinite number of latent communities. The communities are allowed to overlap with each other, with a community's overlapping parts assumed to be more densely connected than its non-overlapping ones. The model is evaluated with synthetic data to illustrate its ability to model assortative networks and its restriction on modeling dissortative ones.
引用
收藏
页码：2776 / 2780
页数：5
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