A Visual Analytics Approach for Structural Differences among Transportation Networks. Issue 5 (2020) - Han, Dongming; Pan, Jiacheng; Xie, Cong; Zhao, Xiaodong; Chen, Wei
Abstract: Representing and analyzing structural differences among transportation networks help gain insight into the difference related patterns such as dynamic evolutions of transportation networks. Conventional solutions leverage representation learning techniques to encode structural information, but lack of an intuitive way of studying structural semantics of transportation networks. In this paper, we propose a representation-and-analysis scheme for structural differences among graphs. We propose a Delta2vec embedding technique to encode multiple graphs while preserving semantics of structural differences. We design and implement a web-based visual analytics system to support comparative study of features learned from the embeddings. One distinctive feature of our approach is that it supports semantics-aware construction, quantification, and investigation of latent relations encoded in graphs.