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EvoGraph:一种有效的保持图财产的图升级方法

EvoGraph: An Effective and Efficient Graph Upscaling Method for Preserving Graph Properties
课程网址: http://videolectures.net/kdd2018_park_evograph_method/  
主讲教师: Himchan Park
开课单位: 大邱庆北科学技术研究所(DGIST)
开课时间: 2018-11-23
课程语种: 英语
中文简介:
如今,许多研究人员和行业团体经常因缺乏各种大型真实图而苦恼。虽然已经开发了许多合成图生成方法(或模型),如RMAT和BA,但它们的输出图在图的财产方面往往与实际图有很大的不同。有一些图形升级方法,例如Gscaler,它们仍然无法保留原始图形的重要财产,并且由于内存不足或运行时间过长而无法升级。在本文中,我们提出了一种称为EvoGraph的新的图升级方法,该方法可以在不考虑比例因子的情况下保持原始图的财产,从而对原始图进行升级。它使用优先附着机制以有效和高效的方式确定并将新边附着到真实图。通过大量实验,我们证明EvoGraph在保留图形财产和性能度量(如运行时、内存使用和可伸缩性)方面显著优于最先进的图形升级方法Gscaler
课程简介: Nowadays, many researchers and industry groups often suffer from the lack of a variety of large-scale real graphs. Although a lot of synthetic graph generation methods (or models) such as RMAT and BA have been developed, their output graphs tend to be quite different from real-world graphs in terms of graph properties. There are a few graph upscaling methods such as Gscaler, they still fail to preserve important properties of the original graph and fail to upscale due to out of memory or too long runtime. In this paper, we propose a novel graph upscaling method called EvoGraph that can upscale the original graph with preserving its properties regardless of a scale factor. It determines and attaches new edges to the real graph using the preferential attachment mechanism in an effective and efficient way. Through extensive experiments, we have demonstrated that EvoGraph significantly outperforms the state-of-the-art graph upscaling method Gscaler in terms of preserving graph properties and performance measures such as runtime, memory usage, and scalability
关 键 词: EvoGraph; 有效的保持图财产; 图升级方法; 保留图形财产和性能度量
课程来源: 视频讲座网
数据采集: 2023-03-09:cyh
最后编审: 2023-05-15:cyh
阅读次数: 37