论文标题
稀疏图的快速图形变换
Fast Graphlet Transform of Sparse Graphs
论文作者
论文摘要
我们介绍了稀疏大图的Graphlet变换的计算问题。图形是所有图形/网络的基本拓扑元素。它们可以用作编码元素，以在多个粒度级别上编码图形信息，以分类同一图/网络上的顶点，以及在不同网络上进行分化或连接。使用Graphlets的网络/图形分析具有增长的应用程序。我们认识到使用多个Graphlet时的通用性和增加的编码能力，我们解决了出现的计算复杂性问题，并提出了一种快速的方法，用于精确的Graphlet Transform。快速的GraphLet变换以高计算效率，低内存消耗以及现成的转换为高性能计划和实现，立即建立了一些出色的记录。它旨在使用Graphlet启用和提高网络/图形分析，并将相对较新的分析设备引入图理论，高性能图计算和更广泛的应用程序。
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.
