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arXiv · 2508.17013

Dense Subgraph Clustering and a New Cluster Ensemble Method

The-Anh Vu-Le·João Alfredo Cardoso Lamy·Tomás Alessi·Ian Chen·Minhyuk Park·Elfarouk Harb·George Chacko·Tandy Warnow
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Abstract

We propose DSC-Flow-Iter, a new community detection algorithm that is based on iterative extraction of dense subgraphs. Although DSC-Flow-Iter leaves many nodes unclustered, it is competitive with leading methods and has high-precision and low-recall, making it complementary to modularity-based methods that typically have high recall but lower precision. Based on this observation, we introduce a novel cluster ensemble technique that combines DSC-Flow-Iter with modularity-based clustering, to provide improved accuracy. We show that our proposed pipeline, which uses this ensemble technique, outperforms its individual components and improves upon the baseline techniques on a large collection of synthetic networks.

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The-Anh Vu-Le, João Alfredo Cardoso Lamy, Tomás Alessi, Ian Chen, Minhyuk Park, Elfarouk Harb, George Chacko, Tandy Warnow. 2025-08-23. Dense Subgraph Clustering and a New Cluster Ensemble Method. https://arxiv.org/abs/2508.17013

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