Latent Multi-Group Membership Graph Model
Abstract
We develop the Latent Multi-group Membership Graph (LMMG) model, a model of networks with rich node feature structure. In the LMMG model, each node belongs to multiple groups and each latent group models the occurrence of links as well as the node feature structure. The LMMG can be used to summarize the network structure, to predict links between the nodes, and to predict missing features of a node. We derive efficient inference and learning algorithms and evaluate the predictive performance of the LMMG on several social and document network datasets.
Cite
Text
Kim and Leskovec. "Latent Multi-Group Membership Graph Model." International Conference on Machine Learning, 2012.Markdown
[Kim and Leskovec. "Latent Multi-Group Membership Graph Model." International Conference on Machine Learning, 2012.](https://mlanthology.org/icml/2012/kim2012icml-latent/)BibTeX
@inproceedings{kim2012icml-latent,
title = {{Latent Multi-Group Membership Graph Model}},
author = {Kim, Myunghwan and Leskovec, Jure},
booktitle = {International Conference on Machine Learning},
year = {2012},
url = {https://mlanthology.org/icml/2012/kim2012icml-latent/}
}