iGraphMatch is an R package for finding corresponding vertices between two graphs, also known as graph matching. The package implements three categories of prevalent graph matching algorithms including relaxation-based, percolation-based, and spectral-based, which are applicable to matching graphs under general settings: weighted directed graphs of different order and graphs of multiple layers. We provide versatile options to incorporate prior information in the form of seeds with or without noise and similarity scores. In addition, iGraphMatch provides functions to summarize the graph matching results in terms of several evaluation measures and visualize the matching performance. Finally, the package enables users to sample correlated random graph pairs from classic random graph models to generate data for simulations. This paper illustrates the practical applications of the package to the analysis of graph matching by detailed examples using real data from communication, neuron, and transportation networks.
翻译:iGraphMatch 是用于在两个图表(又称图表匹配)之间寻找对应的脊椎的R包件。该包件执行三种通用的图形匹配算法,包括基于放松、渗透和光谱的算法,这些算法适用于一般设置下的匹配图:不同顺序的加权定向图表和多层的图表。我们提供了多种选项,以种子或无噪音和类似分数的形式纳入先前的信息。此外, iGraphMatch提供函数,以若干评估措施来概括图形匹配结果,并将匹配性能可视化。 最后,该包件使用户能够从经典随机图表模型中抽取相关随机图表对子样本,为模拟生成数据。本文用通信、神经和运输网络中的真实数据,用详细的例子来说明该包件对图表匹配分析的实用应用。