2.1 Mixed-Membership Stochastic Block-Models for Transactional Data

2 janvier 2017
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Transactional network data arise in many fields. Although social network models have been applied to transactional data, these models typically assume binary relations between pairs of nodes. We develop a latent mixed membership model capable of modelling richer forms of transactional data. Estimation and inference are accomplished via a variational EM algorithm. Simulations indicate that the learning algorithm can recover the correct generative model. We further present results on a subset of the Enron email dataset. This is a joint work with Mahdi Shafiei.