论文标题
量化图数据上近似模拟的框架
A Framework to Quantify Approximate Simulation on Graph Data
论文作者
论文摘要
仿真及其变体（例如，仿真和具有学位的模拟）在广泛的应用中很有用。但是，所有仿真变体都是粗糙的“ Yes-or-No”指标，这些指标只需确认或反驳一个节点是否模拟另一个节点，这限制了其实用程序的范围和功能。因此，开发分数$χ$仿真度量以量化一个节点通过模拟变体$χ$模拟另一个节点的程度是有意义的。为此，我们首先介绍了分数$χ$仿真度量所需的几个属性。然后，我们提出$fsim_χ$，这是一种一般的分数$χ$仿真计算框架，可以配置以量化所有$χ$ sifulations的程度。全面的实验和现实的案例研究表明，该措施是有效的，计算框架是有效的。
Simulation and its variants (e.g., bisimulation and degree-preserving simulation) are useful in a wide spectrum of applications. However, all simulation variants are coarse "yes-or-no" indicators that simply confirm or refute whether one node simulates another, which limits the scope and power of their utility. Therefore, it is meaningful to develop a fractional $χ$-simulation measure to quantify the degree to which one node simulates another by the simulation variant $χ$. To this end, we first present several properties necessary for a fractional $χ$-simulation measure. Then, we present $FSim_χ$, a general fractional $χ$-simulation computation framework that can be configured to quantify the extent of all $χ$-simulations. Comprehensive experiments and real-world case studies show the measure to be effective and the computation framework to be efficient.
