# Clustering of check-in sequences using the mixture Markov chain process

arXiv: https://arxiv.org/abs/2106.12039 · HTML: https://mlsanity.com/paper/2106.12039/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 6 references that are in the map.
- First posted on arXiv 16 Jun 2021.

## Builds on (most cited first, 1 of 1)

- [Sequences of purchases in credit card data reveal life styles in urban populations](https://mlsanity.com/paper/1703.00409/) (2017)

## Abstract (arXiv)

This work is devoted to the clustering of check-in sequences from a geosocial network. We used the mixture Markov chain process as a mathematical model for time-dependent types of data. For clustering, we adjusted the Expectation-Maximization (EM) algorithm. As a result, we obtained highly detailed communities (clusters) of users of the now defunct geosocial network, Weeplaces.