An Effective Resistance based Genetic Algorithm for Community Detection

Clara Pizzuti, Annalisa Socievole

2021

Abstract

This work presents a new approach based on genetic algorithms (GAs) and the concept of effective resistance for detecting communities within an undirected graph. The method considers the equivalent electric network of the input graph, where edges are weighted with their effective resistance, a measure of electrical resistance between nodes, whose square root has been shown to be a Euclidean metric. The algorithm computes the similarity between nodes by using the effective resistance values and generates a weighted and sparse graph by adopting a thresholding sparsification strategy based on the nearest neighbors of each node. Experiments over synthetic and real-world networks demonstrate the effectiveness of our approach when compared to other benchmark methods.

Paper Citation

in Harvard Style

Pizzuti C. and Socievole A. (2021). An Effective Resistance based Genetic Algorithm for Community Detection. In Proceedings of the 13th International Joint Conference on Computational Intelligence (IJCCI 2021) - Volume 1: IJCCI; ISBN 978-989-758-534-0, SciTePress, pages 28-36. DOI: 10.5220/0010644300003063

in Bibtex Style

@conference{ijcci21,
author={Clara Pizzuti and Annalisa Socievole},
title={An Effective Resistance based Genetic Algorithm for Community Detection},
booktitle={Proceedings of the 13th International Joint Conference on Computational Intelligence (IJCCI 2021) - Volume 1: IJCCI},
year={2021},
pages={28-36},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010644300003063},
isbn={978-989-758-534-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computational Intelligence (IJCCI 2021) - Volume 1: IJCCI
TI - An Effective Resistance based Genetic Algorithm for Community Detection
SN - 978-989-758-534-0
AU - Pizzuti C.
AU - Socievole A.
PY - 2021
SP - 28
EP - 36
DO - 10.5220/0010644300003063
PB - SciTePress