App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 8

SDFC: hierarchical graph summarization model based on topological structures

Zhao Danfeng1
Shen Dong1
Ma Jian2
Wang Jian1
He Qi1
1. College of Information Technology, Shanghai Ocean University, Shanghai 201306, China
2. Shanghai Asia-Pacific Typhoon Research Center, Shanghai 201306, China
DOI: 10.19734/j.issn.1001-3695.2025.12.0511

Abstract

This paper proposes a topology-based hierarchical graph summarization model (SDFC) to address the high storage overhead of large-scale graph data and the lack of structural interpretability in existing methods. The model formalized graph understanding as a recursive process from micro-topology to macro-organization. First, the method constructed supernodes by partitioning communities and identifying six basic topological structures, including cliques, bipartite cores, stars, and chains. Then, it filtered optimal structures based on a revenue evaluation function and applied a positive and negative edge mechanism to uniformly represent superedges and single edges, achieving completely lossless compression of the original graph. Finally, the algorithm adopted a hierarchical processing strategy to deeply mine complex nested relationships in graph data by adaptively and recursively merging topological structures. Experimental results on six real-world datasets showed that the algorithm achieved an average compression ratio of 0.5269. Compared with advanced algorithms such as HVoS, Slugger, and MAGS, its compression efficiency improved by 12.6%, 28.4%, and 17.8%, respectively, while maintaining a controllable time complexity. The SDFC model effectively breaks the barrier between storage efficiency and understanding depth. It significantly reduces storage costs while revealing the multidimensional hierarchical characteristics and intrinsic topological patterns of graph data.

Foundation Support

国家自然科学基金资助项目(42376194)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.12.0511
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 8

Publish History

[2026-04-22] Accepted Paper

Cite This Article

赵丹枫, 沈栋, 马健, 等. SDFC：基于拓扑结构的层次图摘要模型 [J]. 计算机应用研究, 2026, 43 (8). (2026-04-30). https://doi.org/10.19734/j.issn.1001-3695.2025.12.0511. (Zhao Danfeng, Shen Dong, Ma Jian, et al. SDFC: hierarchical graph summarization model based on topological structures [J]. Application Research of Computers, 2026, 43 (8). (2026-04-30). https://doi.org/10.19734/j.issn.1001-3695.2025.12.0511. )

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  • Application Research of Computers Monthly Journal
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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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