Abstract
Heterogeneity characterises real-world networks, where nodes show a broad range of different topological features. However, nodes also tend to organise into communities – subsets of nodes that are sparsely inter-connected but are densely intra-connected (more than the network’s average connectivity). This means that nodes belonging to the same community are close to each other by some distance measure, such as the resistance distance, which is the effective distance between any pair of nodes considering all possible paths. In this work, we present automation (i.e., unsupervised) and missing accuracy tests for a recently proposed semi-supervised community detection algorithm based on the resistance distance. The accuracy testing involves quantifying our algorithm’s performance in terms of recovering known synthetic communities from benchmark networks, where we present results for Girvan-Newman and Lancichinetti-Fortunato-Radicchi networks. Our findings show that our algorithm falls into the class of fairly accurate performers.
Original language | English |
---|---|
Title of host publication | Complex Networks and Their Applications X - Proceedings of the 10th International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2021 |
Editors | Rosa Maria Benito, Chantal Cherifi, Hocine Cherifi, Esteban Moro, Luis M. Rocha, Marta Sales-Pardo |
Publisher | Springer Science and Business Media Deutschland GmbH |
Pages | 309-320 |
Number of pages | 12 |
Volume | 1015 |
ISBN (Print) | 9783030934088 |
DOIs | |
Publication status | Published - 2022 |
Event | 10th International Conference on Complex Networks and Their Applications, COMPLEX NETWORKS 2021 - Madrid, Spain Duration: 30 Nov 2021 → 2 Dec 2021 |
Publication series
Name | Studies in Computational Intelligence |
---|---|
Volume | 1015 |
ISSN (Print) | 1860-949X |
ISSN (Electronic) | 1860-9503 |
Conference
Conference | 10th International Conference on Complex Networks and Their Applications, COMPLEX NETWORKS 2021 |
---|---|
Country/Territory | Spain |
City | Madrid |
Period | 30/11/21 → 2/12/21 |
Keywords
- Benchmark tests
- Community detection
- Resistance distance
Fingerprint
Dive into the research topics of 'Community Detection by Resistance Distance: Automation and Benchmark Testing'. Together they form a unique fingerprint.Equipment
-
Aberdeen Biomedical Imaging Centre
Gordon Waiter (Manager) & Teresa Morris (Facilities Co-ordinator)
Aberdeen Biomedical Imaging CentreResearch Facilities: Facility