# Finding compact communities in large graphs

arXiv: https://arxiv.org/abs/1410.2105 · HTML: https://mlsanity.com/paper/1410.2105/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Oct 2014.

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

- [Community Detection for Heterogeneous Multiple Social Networks](https://mlsanity.com/paper/2405.04371/) (2024)

## Abstract (arXiv)

This article presents an efficient hierarchical clustering algorithm that solves the problem of core community detection. It is a variant of the standard community detection problem in which we are particularly interested in the connected core of communities. To provide a solution to this problem, we question standard definitions on communities and provide alternatives. We also propose a function called compactness, designed to assess the quality of a solution to this problem. Our algorithm is based on a graph traversal algorithm, the LexDFS. The time complexity of our method is in O(n× log(n)). Experiments show that our algorithm creates highly compact clusters.