# COHORTNEY: Non-Parametric Clustering of Event Sequences

arXiv: https://arxiv.org/abs/2104.01440 · HTML: https://mlsanity.com/paper/2104.01440/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 23 references that are in the map.
- First posted on arXiv 3 Apr 2021.

## Built on by (most cited first, 1 of 1)

- [Continuous-time convolutions model of event sequences](https://mlsanity.com/paper/2302.06247/) (2023)

## Abstract (arXiv)

Cohort analysis is a pervasive activity in web analytics. One divides users into groups according to specific criteria and tracks their behavior over time. Despite its extensive use, academic circles do not discuss cohort analysis to evaluate user behavior online. This work introduces an unsupervised non-parametric approach to group Internet users based on their activities. In comparison, canonical methods in marketing and engineering-based techniques underperform. COHORTNEY is the first machine learning-based cohort analysis algorithm with a robust theoretical explanation.