基于图熵编码的城市空间节点发现
Discovering Important Nodes Through Graph Entropy Encoded in Urban Space Syntax
摘要：
城市空间网络中的潜在影响空间可以通过熵参与率来检测。被认为是本地（连接）和全球（中心）熵。随着城市规模的增大，城市的连通性熵有增大的趋势，而反映城市整体连通性的中心性熵则呈减小的趋势。在城市网络中，节点的局部属性和全局属性正相关，这表明城市的可理解性。熵参与率之间的相关性可以用于可懂度测量和城市网络比较的目的。
英文摘要：
Potentially influential spaces in the spatial networks of cities can be detected by means of the entropy participation ratios. Local (connectivity) and global (centrality) entropies are considered. While the connectivity entropy has a tendency to increase with the city size, the centrality entropy is decreasing that reflects the global connectedness of cities. In urban networks, the local and global properties of nodes are positively correlated that indicates the intelligibility of cities. Correlations between entropy participation ratios can be used in purpose of intelligibility measurements and city networks comparisons.
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。
