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Mixed-Membership Stochastic Block-Models for Transactional Networks
2010 IEEE International Conference on Data Mining
Transactional network data can be thought of as a list of one-to-many communications (e.g., email) between nodes in a social network. Most social network models convert this type of data into binary relations between pairs of nodes. We develop a latent mixed membership model capable of modeling richer forms of transactional network data, including relations between more than two nodes. The model can cluster nodes and predict transactions. The block-model nature of the model implies that groupsdoi:10.1109/icdm.2010.88 dblp:conf/icdm/ShafieiC10 fatcat:tjuzo66lfzfxffrbalntoxvvty