Linear Clustering Process on Networks

Linear Clustering Process on Networks

Jokic, I. (TU Delft Network Architectures and Services)
Van Mieghem, P.F.A. (TU Delft Network Architectures and Services)

2023

We propose a linear clustering process on a network consisting of two opposite forces: attraction and repulsion between adjacent nodes. Each node is mapped to a position on a one-dimensional line. The attraction and repulsion forces move the nodal position on the line, depending on how similar or different the neighbourhoods of two adjacent nodes are. Based on each node position, the number of clusters in a network and each node's cluster membership is estimated. The performance of the proposed linear clustering process is benchmarked on synthetic networks against widely accepted clustering algorithms such as modularity, Leiden method, Louvain method and the non-back tracking matrix. The proposed linear clustering process outperforms the most popular modularity-based methods, such as the Louvain method, on synthetic and real-world networks, while possessing a comparable computational complexity.

Communities
graph clustering
modularity
linear process

http://resolver.tudelft.nl/uuid:a6b222eb-fa9b-4157-9bb7-c0e181f7c471

https://doi.org/10.1109/TNSE.2023.3271360

2023-11-01

2327-4697

IEEE Transactions on Network Science and Engineering, 10 (6), 3697 - 3706

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

journal article

© 2023 I. Jokic, P.F.A. Van Mieghem