用树图学习图表示
Learning Graph Representations by Dendrograms
摘要：
层次图聚类是揭示复杂网络多尺度结构的常用方法。我们提出了一个新的度量评估质量的层次聚类。该度量反映了从树状图重建图的能力，树状图对层次结构进行编码。图的最佳表示定义了一类可约的联系，导致规则的树图贪婪凝聚聚类。
英文摘要：
Hierarchical graph clustering is a common technique to reveal the multi-scale structure of complex networks. We propose a novel metric for assessing the quality of a hierarchical clustering. This metric reflects the ability to reconstruct the graph from the dendrogram, which encodes the hierarchy. The optimal representation of the graph defines a class of reducible linkages leading to regular dendrograms by greedy agglomerative clustering.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
