VGM:可视化图形挖掘

K. Borgwardt, Sebastian Böttger, H. Kriegel
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引用次数: 1

摘要

随着越来越多的图数据被应用于各个应用领域,图挖掘在数据管理中的重要性日益凸显。图核是一种新颖而成功的图数据挖掘方法。不幸的是,实现图核并不简单,因此到目前为止很少有应用研究人员使用图核。在这个演示中,我们展示了一个名为Visual Graph Mining (VGM)的Java软件包。VGM允许用户在易于学习和使用的图形用户界面中使用图形核和支持向量机对图形进行分类。它链接到LIBSVM支持向量机计算,但可以很容易地转移到其他支持向量机软件包。此外,VGM还提供了最近邻搜索等基本数据挖掘功能,Dijkstra、Floyd-Warshall等图算法,并计算和可视化产品图和图的拓扑索引。VGM的主页是:http://www.cip.ifi.lmu.de/~boettger/sigmod。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
VGM: visual graph mining
As more and more graph data become available in various application domains, graph mining is of ever increasing importance in data management.Graph kernels are a novel and successful method for data mining in graphs. Unfortunately, implementing graph kernels is not trivial, and few applied researchers have therefore used graph kernels so far. In this demonstration, we present a Java software package called Visual Graph Mining (VGM). VGM allows the user to classify graphs using graph kernels and Support Vector Machines in a graphical user interface that is easy to learn and use. It is linked to LIBSVM for Support Vector Machine computations, yet can be easily transferred to other Support Vector Machine packages. Furthermore, VGM provides basic data mining features such as Nearest Neighbor search, graph algorithms such as Dijkstra, Floyd-Warshall, and computes and visualizes product graphs and topological indices of graphs.VGM 's homepage can be found at: http://www.cip.ifi.lmu.de/~boettger/sigmod.
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