可扩展性
计算机科学
稳健性(进化)
估计员
诱导子图同构问题
理论计算机科学
图形
大数据
人工智能
数学
数据挖掘
折线图
统计
基因
数据库
化学
生物化学
电压图
作者
Hanchen Wang,Rong Hu,Ying Zhang,Lu Qin,Wei Wang,Wenjie Zhang
标识
DOI:10.1145/3514221.3526163
摘要
Subgraph counting is a fundamental graph analysis task which has been widely used in many applications. As the problem of subgraph counting is NP-complete and hence intractable, approximate solutions have been widely studied, which fail to work with large and complex query graphs. Alternatively, Machine Learning techniques have been recently applied for this problem, yet the existing ML approaches either only support very small data graphs or cannot make full use of the data graph information, which inherently limits their scalability, estimation accuracies and robustness.
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