A Parallel Hierarchical Approach for Community Detection on Large-scale Dynamic Networks
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866913707320147968 |
|---|---|
| author | Bokov, Grigoriy Konovalov, Aleksandr Uporova, Anna Moiseev, Stanislav Safonov, Ivan Radionov, Alexander |
| author_facet | Bokov, Grigoriy Konovalov, Aleksandr Uporova, Anna Moiseev, Stanislav Safonov, Ivan Radionov, Alexander |
| contents | In this paper, we propose a novel parallel hierarchical Leiden-based algorithm for dynamic community detection. The algorithm, for a given batch update of edge insertions and deletions, partitions the network into communities using only a local neighborhood of the affected nodes. It also uses the inner hierarchical graph-based structure, which is updated incrementally in the process of optimizing the modularity of the partitioning. The algorithm has been extensively tested on various networks. The results demonstrate promising improvements in performance and scalability while maintaining the modularity of the partitioning. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_18497 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Parallel Hierarchical Approach for Community Detection on Large-scale Dynamic Networks Bokov, Grigoriy Konovalov, Aleksandr Uporova, Anna Moiseev, Stanislav Safonov, Ivan Radionov, Alexander Social and Information Networks Distributed, Parallel, and Cluster Computing Discrete Mathematics In this paper, we propose a novel parallel hierarchical Leiden-based algorithm for dynamic community detection. The algorithm, for a given batch update of edge insertions and deletions, partitions the network into communities using only a local neighborhood of the affected nodes. It also uses the inner hierarchical graph-based structure, which is updated incrementally in the process of optimizing the modularity of the partitioning. The algorithm has been extensively tested on various networks. The results demonstrate promising improvements in performance and scalability while maintaining the modularity of the partitioning. |
| title | A Parallel Hierarchical Approach for Community Detection on Large-scale Dynamic Networks |
| topic | Social and Information Networks Distributed, Parallel, and Cluster Computing Discrete Mathematics |
| url | https://arxiv.org/abs/2502.18497 |