# Dynamic Infinite Mixed-Membership Stochastic Blockmodel

arXiv: https://arxiv.org/abs/1306.2999 · HTML: https://mlsanity.com/paper/1306.2999/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Jun 2013.

## Built on by (most cited first, 2 of 2)

- [Dynamic Mixed Membership Stochastic Block Model for Weighted Labeled Networks](https://mlsanity.com/paper/2304.05894/) (2023)
- [Hierarchical Blockmodelling for Knowledge Graphs](https://mlsanity.com/paper/2408.15649/) (2024)

## Abstract (arXiv)

Directional and pairwise measurements are often used to model inter-relationships in a social network setting. The Mixed-Membership Stochastic Blockmodel (MMSB) was a seminal work in this area, and many of its capabilities were extended since then. In this paper, we propose the Dynamic Infinite Mixed-Membership stochastic blockModel (DIM3), a generalised framework that extends the existing work to a potentially infinite number of communities and mixture memberships for each of the network's nodes. This model is in a dynamic setting, where additional model parameters are introduced to reflect the degree of persistence between one's memberships at consecutive times. Accordingly, two effective posterior sampling strategies and their results are presented using both synthetic and real data.