A PROBABILISTIC EMBEDDING CLUSTERING METHOD FOR URBAN STRUCTURE DETECTION

6 citations as recorded by crossref.

1. Identifying the Structure of Cities by Clustering Using a New Similarity Measure Based on Smart Card Data K. Kim
2. Reasoning about socio-economic data: a visual analytics approach to Bayesian network E. Chuprikova & L. Meng
3. Anchor-Enhanced Geographical Entity Representation Learning R. Chen et al.
4. Multi‐graph convolutional clustering network B. Wang et al.
5. Activity-aware urban area embedding with contrastive learning for intelligent transportation systems applications G. Li et al.
6. Integrating Gaussian Mixture Dual-Clustering and DBSCAN for Exploring Heterogeneous Characteristics of Urban Spatial Agglomeration Areas T. Xiao et al.