Difference between revisions of "M. Kim and J. Leskovec. ICML'12"
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== Summary == | == Summary == | ||
This is a paper on block based network analysis and prediction. This work furthers the work by Airoldi. et. al (see Related papers) to the | This is a paper on block based network analysis and prediction. This work furthers the work by Airoldi. et. al (see Related papers) to the | ||
| − | extent that each node/ user can actually belong to more than one block. | + | extent that each node/ user can actually belong to more than one block and node features are modeled in addition to link existence. The generative process is given as below (see the figure) |
| + | |||
| + | [[File:KimLeskovec.png] ] | ||
| + | |||
== Dicussion == | == Dicussion == | ||
Revision as of 13:09, 2 October 2012
This is a scientific paper authored by M. Kim and J. Leskovec, and appeared in ICML'12. Below is the paper summary written by Tuan Anh.
Citation
Online Version
Latent Multi-group Membership Graph Model.
Summary
This is a paper on block based network analysis and prediction. This work furthers the work by Airoldi. et. al (see Related papers) to the extent that each node/ user can actually belong to more than one block and node features are modeled in addition to link existence. The generative process is given as below (see the figure)
[[File:KimLeskovec.png] ]
Dicussion
Related papers
- Probabilistic graph clustering: Airoldi. et. al. Mixed Membership Stochastic Blockmodels. Journal of Machine Learning Research 9 (2008) 1981-2014
- The paper by Hoff on Multiplicative latent factor models for description and prediction of social networks
