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- research-articleDecember 2023
Towards Generative Modeling of Urban Flow through Knowledge-enhanced Denoising Diffusion
SIGSPATIAL '23: Proceedings of the 31st ACM International Conference on Advances in Geographic Information SystemsArticle No.: 91, Pages 1–12https://doi.org/10.1145/3589132.3625641Although generative AI has been successful in many areas, its ability to model geospatial data is still underexplored. Urban flow, a typical kind of geospatial data, is critical for a wide range of applications from public safety and traffic management ...
- research-articleNovember 2019
Matrix Factorization for Spatio-Temporal Neural Networks with Applications to Urban Flow Prediction
CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge ManagementPages 2683–2691https://doi.org/10.1145/3357384.3357832Predicting urban flow is essential for city risk assessment and traffic management, which profoundly impacts people's lives and property. Recently, some deep learning models, focusing on capturing spatio-temporal (ST) correlations between urban regions, ...
- extended-abstractSeptember 2016
Visualizing mobile phone usage for exploratory analysis: a case study of portugal
UbiComp '16: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: AdjunctPages 1358–1362https://doi.org/10.1145/2968219.2968413This paper presents a visualization tool for mobile phone usage analysis. Data of mobile phone usage from Portugal is used for demonstration. The visualization runs on two modes: Flow and Intensity. Flow mode displays a 3D animation of mobile phone ...