Multi-attribute network refers to network data with multiple attribute views and relational view. Although semi-supervised collective classification has been investigated extensively, little attention is received for such kind of network data. We have proposed an effective generative model with network regularization for multi-attribute and relational learning (MARL). This model is not only able to effectively exploit the information contained in different types of attribute views, but also incorporate the network structure information for prediction.
% The code has been used in:
% [1] Wang S, Ye Y, Li X, et al. Semi-supervised Collective Classification in Multi-attribute Network Data. Neural Process Lett (2016). doi:10.1007/s11063-016-9517-y
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