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New vertex ordering method boosts graph compression efficiency

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new vertex ordering method called Leiden+LLP for graph compression, which improves efficiency by analyzing community structures within the graph. This approach demonstrated significant savings, reducing bits per edge by 0.3 to 5.4 across various datasets and compression encoders. The study also introduced three new reference-based encoders (BG, CS, and CG) that offer further compression gains over existing methods, with the potential for low-overhead random access. AI

IMPACT Improves efficiency for graph compression techniques, potentially impacting data handling in AI systems.

RANK_REASON The cluster contains an academic paper detailing a new method and empirical study. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New vertex ordering method boosts graph compression efficiency

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The cluster contains an academic paper detailing a new method and empirical study. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Jimmy Dubuisson ·

    Community-Aware Vertex Ordering for Reference-Based Graph Compression: A Cross-Encoder Empirical Study

    arXiv:2605.21510v1 Announce Type: cross Abstract: Reference-based graph compression encodes each vertex's neighbor list relative to a recent vertex, exploiting locality to compress large directed graphs. The dominant tool, WebGraph's BVGraph, fixes a single encoding pipeline and …

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