论文标题
逻辑网络结构编码的大图的基于prufer序列的表示
A Prufer-Sequence Based Representation of Large Graphs for Structural Encoding of Logic Networks
论文作者
论文摘要
当今现实生活系统中图的普遍性是很明显的，在该系统中，该系统要么明确地存在图形，要么可以很容易地将其建模为一个。因此，这种图形结构是商店丰富的信息。这具有各种含义，具体取决于我们对节点还是整个图表感兴趣。在本文中，我们主要关注的是较晚的，即图表的结构影响其代表的现实生活系统的属性。这种结构影响的模型将通过其结构特性来推断复杂和大型系统（例如VLSI电路）的有用特性。但是，在我们可以将基于机器学习（ML）技术应用于建模这种关系之前，必须有效地表示图。在本文中，我们提出了一个图表表示，该图表是无损的，在顶点数量方面是线性大小的，并给出图表的1-D表示。我们的表示是基于对树木编码的Prufer编码。此外，我们的方法基于一种新颖的技术，称为$ \ Mathcal {gt} $ - 增强功能，我们首先将图形转换为以奇异树的形式来表示。编码还提供了包括其他图形属性并改善代码的解释性的范围。
The pervasiveness of graphs in today's real life systems is quite evident, where the system either explicitly exists as graph or can be readily modelled as one. Such graphical structure is thus a store house rich information. This has various implication depending on whether we are interested in a node or the graph as a whole. In this paper, we are primarily concerned with the later, that is, the inference that the structure of the graph influences the property of the real life system it represents. A model of such structural influence would be useful in inferencing useful properties of complex and large systems, like VLSI circuits, through its structural property. However, before we can apply some machine learning (ML) based technique to model such relationship, an effective representation of the graph is imperative. In this paper, we propose a graph representation which is lossless, linear-sized in terms of number of vertices and gives a 1-D representation of the graph. Our representation is based on Prufer encoding for trees. Moreover, our method is based on a novel technique, called $\mathcal{GT}$-enhancement whereby we first transform the graph such that it can be represented by a singular tree. The encoding also provides scope to include additional graph property and improve the interpretability of the code.
