1. Andrienko NV, Andrienko GL (2011) Spatial generalization and aggregation of massive movement data. IEEE Trans Vis Comput Graph 17(2):205–219
2. Chen Z, Ding Z (2019) Improved word representation based on glove model. Comput Syst Appl 28(1):194–199
3. Chen W, Huang Z, Wu F, Zhu M, Guan H, Maciejewski R (2018) VAUD: a visual analysis approach for exploring spatio-temporal urban data. IEEE Trans Vis Comput Graph 24(9):2636–2648
4. Chu D, Sheets DA, Zhao Y, Wu Y, Yang J, Zheng M, Chen G (2014) Visualizing hidden themes of taxi movement with semantic transformation. In: IEEE pacific visualization symposium, PacificVis 2014, Yokohama, Japan, March 4–7, 2014. IEEE Computer Society, pp 137–144
5. Feng S, Cong G, An B, Chee YM (2017) Poi2vec: geographical latent representation for predicting future visitors. In: Singh SP, Markovitch S (eds) Proceedings of the thirty-first AAAI conference on artificial intelligence, February 4–9, 2017, San Francisco, California, USA. AAAI Press, pp 102–108