MC-Explorer: Analyzing and Visualizing Motif-Cliques on Large Networks

2020 IEEE 36th International Conference on Data Engineering (ICDE) Pub Date : 2020-04-01 DOI:10.1109/ICDE48307.2020.00154

Boxuan Li, Reynold Cheng, Jiafeng Hu, Yixiang Fang, Min Ou, Ruibang Luo, K. Chang, Xuemin Lin

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引用次数: 4

Abstract

Large networks with labeled nodes are prevalent in various applications, such as biological graphs, social networks, and e-commerce graphs. To extract insight from this rich information source, we propose MC-Explorer, which is an advanced analysis and visualization system. A highlight of MC-Explorer is its ability to discover motif-cliques from a graph with labeled nodes. A motif, such as a 3-node triangle, is a fundamental building block of a graph. A motif-clique is a "complete" subgraph in a network with respect to a desired higher-order connection pattern. For example, on a large biological graph, we found out some motif-cliques, which disclose new side effects of a drug, and potential drugs for healing diseases. MC-Explorer includes online and interactive facilities for exploring a large labeled network through the use of motif-cliques. We will demonstrate how MC-Explorer can facilitate the analysis and visualization of a labeled biological network.An online demo video of MC-Explorer can be accessed from https://www.dropbox.com/s/vkalumc28wqp8yl/demo.mov

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MC-Explorer:分析和可视化大型网络上的主题集团

带有标记节点的大型网络在各种应用中都很流行，例如生物图、社交网络和电子商务图。为了从这个丰富的信息源中提取洞察力，我们提出了MC-Explorer，这是一个先进的分析和可视化系统。MC-Explorer的一个亮点是它能够从带有标记节点的图形中发现主题团。一个主题，如3节点三角形，是图形的基本构建块。基团是网络中相对于期望的高阶连接模式的“完全”子图。例如，在一个大的生物图上，我们发现了一些基序集团，它们揭示了药物的新副作用，以及治疗疾病的潜在药物。MC-Explorer包括在线和交互式设施，用于通过使用主题集团来探索大型标记网络。我们将演示MC-Explorer如何促进标记生物网络的分析和可视化。MC-Explorer的在线演示视频可以从https://www.dropbox.com/s/vkalumc28wqp8yl/demo.mov访问

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2020 IEEE 36th International Conference on Data Engineering (ICDE)

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