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We use barycentric coordinates to embed a graph and its given edge-core partition into a stratified collection of disks. We illustrate this embedding with graphs from social networks (a Friendster graph with 1.8 billion edges), paper citation networks (a Microsoft academic graph with 1.6 billion edges), and social media posts (Parler with 1.1 million edges, French election data with 185 thousand edges, and COVID-19 with 18 thousand edges). The proposed embedding aggregates vertices with similar participation in the input edge-core partition, and this similarity can be used to support subset queries useful for making sense of billion-edge graph data.

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Stratified Disk Views of Graph Edge Core Decompositions via Barycentric Coordinates

  • 会议论文

  • 发表日期：

    2026年

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  • James Abello,
  • Haoyang Zhang

摘要

We use barycentric coordinates to embed a graph and its given edge-core partition into a stratified collection of disks. We illustrate this embedding with graphs from social networks (a Friendster graph with 1.8 billion edges), paper citation networks (a Microsoft academic graph with 1.6 billion edges), and social media posts (Parler with 1.1 million edges, French election data with 185 thousand edges, and COVID-19 with 18 thousand edges). The proposed embedding aggregates vertices with similar participation in the input edge-core partition, and this similarity can be used to support subset queries useful for making sense of billion-edge graph data.