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A Survey on Methods and Systems for Graph Compression

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arxiv 1504.00616 v1 pith:5QTBARKX submitted 2015-04-02 cs.DS

Sebastian Maneth , Fabian Peternek This is my paper · ORCID
classification cs.DS
keywords compressionmethodsgraphsomesurveyaccompanyalgorithmsanother
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We present an informal survey (meant to accompany another paper) on graph compression methods. We focus on lossless methods, briefly list available pproaches, and compare them where possible or give some indicators on their compression ratios. We also mention some relevant results from the field of lossy compression and algorithms specialized for the use on large graphs. --- Note: The comparison is by no means complete. This document is a first draft and will be updated and extended.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 20 citations worldwide. Full citation record

  1. CGS: Configurable Graph Summarization with Bounded Neighborhood Loss and Query Support

    cs.DS 2026-07 conditional novelty 6.0 of 10

    CGS greedily merges nodes with common neighborhoods into three configurable summary variants that bound neighborhood loss and support exact or high-accuracy graph queries without full decompression.

  2. Accelerating Loading WebGraphs in ParaGrapher

    cs.DC 2025-07 conditional novelty 3.0 of 10

    PG-Fuse and CompBin speed up loading of WebGraph-format graphs by up to 7.6x and 21.8x, respectively, on a high-bandwidth shared filesystem.

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