论文标题
图形聚类算法的比较和基准
Comparison and Benchmark of Graph Clustering Algorithms
论文作者
论文摘要
图群集被广泛用于生物网络，社交网络等。十多年来，许多图形聚类算法已经发表，但是尚无全面且一致的性能比较。在本文中，我们对70多个图形聚类程序进行了基准测试，以评估其加权和未加权图的运行时和质量性能。我们还分析了影响性能的地面真理的特征。我们的工作不仅能够为工程师选择聚类算法提供一个起点，而且还可以为研究人员设计新算法提供一个观点。
Graph clustering is widely used in analysis of biological networks, social networks and etc. For over a decade many graph clustering algorithms have been published, however a comprehensive and consistent performance comparison is not available. In this paper we benchmarked more than 70 graph clustering programs to evaluate their runtime and quality performance for both weighted and unweighted graphs. We also analyzed the characteristics of ground truth that affects the performance. Our work is capable to not only supply a start point for engineers to select clustering algorithms but also could provide a viewpoint for researchers to design new algorithms.
