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arXiv · 1703.04943

Matched bipartite block model with covariates

Zahra S. Razaee·Arash A. Amini·Jingyi Jessica Li
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Abstract

Community detection or clustering is a fundamental task in the analysis of network data. Many real networks have a bipartite structure which makes community detection challenging. In this paper, we consider a model which allows for matched communities in the bipartite setting, in addition to node covariates with information about the matching. We derive a simple fast algorithm for fitting the model based on variational inference ideas and show its effectiveness on both simulated and real data. A variation of the model to allow for degree-correction is also considered, in addition to a novel approach to fitting such degree-corrected models.

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Zahra S. Razaee, Arash A. Amini, Jingyi Jessica Li. 2017-03-15. Matched bipartite block model with covariates. https://arxiv.org/abs/1703.04943

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