PulseAugur
实时 08:49:16
English(EN) CGS: Configurable Graph Summarization with Bounded Neighborhood Loss and Query Support

新的CGS框架提供具有边界损失的可配置图摘要

研究人员推出了一种新颖的可配置图摘要框架CGS,旨在应对管理大型图数据集日益增长的挑战。CGS提供三种变体:CGS-E用于无损摘要,CGS-I和CGS-U分别用于具有特定误报或漏报边容忍度的有损摘要。一个关键特性是用户指定的邻域损失容忍度阈值,它限制了重构损失,并确保图查询能够以高准确性和效率得到解答。 AI

排序理由 该集群包含一篇详细介绍新图摘要框架的研究论文。[lever_c_demoted from research: ic=1 ai=0.4]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新的CGS框架提供具有边界损失的可配置图摘要

报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Shubhadip Mitra, Sona Elza Simon, C Oswald, Arnab Bhattacharya, Arindam Pal ·

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

    arXiv:2607.10969v1 Announce Type: cross Abstract: Given a large graph, how to generate a compact summary graph that is configurable by the user and supports multiple graph queries with either no loss or with high accuracy? The ever growing size of graph datasets makes the above q…