稀疏图的快速Graphlet变换
Fast Graphlet Transform of Sparse Graphs
摘要：
介绍了稀疏大型图的图子变换的计算问题。小图是所有图/网络的基本拓扑元素。它们可以被用作编码元素，在多个粒度级别上编码图拓扑信息，用于对同一图/网络上的顶点进行分类，以及用于在不同网络之间进行区分或连接。使用graphlets的网络/图形分析具有越来越多的应用。我们认识到使用多个graphlet的普遍性和增加的编码容量，我们解决了所产生的计算复杂性问题，我们提出了一个快速的方法，精确的graphlet变换。快速graphlet变换建立了几个显着的记录在一次高计算效率，低内存消耗，并准备翻译为高性能的程序和实现。它的目的是启用和推进网络/图形分析与graphlets，并介绍了相对较新的分析设备，图论，高性能图形计算，和更广泛的应用。
英文摘要：
We introduce the computational problem of graphlet transform of a sparse large graph. Graphlets are fundamental topology elements of all graphs/networks. They can be used as coding elements to encode graph-topological information at multiple granularity levels for classifying vertices on the same graph/network as well as for making differentiation or connection across different networks. Network/graph analysis using graphlets has growing applications. We recognize the universality and increased encoding capacity in using multiple graphlets, we address the arising computational complexity issues, and we present a fast method for exact graphlet transform. The fast graphlet transform establishes a few remarkable records at once in high computational efficiency, low memory consumption, and ready translation to high-performance program and implementation. It is intended to enable and advance network/graph analysis with graphlets, and to introduce the relatively new analysis apparatus to graph theory, high-performance graph computation, and broader applications.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
