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October 2, 2025Open Access

GBGC: Efficient and Adaptive Graph Coarsening via Granular-ball Computing

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Authors

SXShuyin XiaGWGuan WangGXG. F. Xu

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Overview

New adaptive graph coarsening method enhances speed and accuracy using multi-granularity techniques.

Key Points

  • This new method of graph coarsening improves both speed and accuracy compared to traditional techniques.
  • Processing speed can increase by tens to hundreds of times while maintaining low time complexity.
  • Granular-ball computing allows adaptive splitting of graphs into supernodes that enhance coarsening precision.
  • The adaptive granular-ball refinement mechanism optimally structures graphs at various levels of granularity.

Cite This Study

Xia et al. (2025) studied this question.

synapsesocial.com/papers/68de84bf5b556a9128e1bd6fhttps://doi.org/10.48550/arxiv.2506.19224
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1GBGC: Efficient and Adaptive Graph Coarsening via Granular-ball Computing2025 · 4 citations
  2. 2GBG++: A Fast and Stable Granular Ball Generation Method for Classification2024 · 78 citations
  3. 3AH-UGC: Adaptive and Heterogeneous-Universal Graph Coarsening2025
  4. 4Multi-granularity collaborative clustering based on adaptive granular-balls2026
  5. 5Generation of Granular-Balls for Clustering Based on the Principle of Justifiable Granularity2024