1. Akbari, M., Samadzadegan, F., & Weibel, R. (2015). A generic regional spatio-temporal co-occurrence pattern mining model: a case study for air pollution. Journal of Geographical Systems, 17(3), 249–274.
2. Arge, L., Procopiuc, O., Ramaswamy, S., et al. (1998). Scalable sweeping-based spatial join. In: Proceedings of VLDB 1998, pp. 570–581
3. Barua, S., & Sander, J. (2014). Mining statistically significant co-location and segregation patterns. IEEE Transactions on Knowledge and Data Engineering (TKDE), 26(5), 1185–1199.
4. Celik, M., Kang, J., & Shekhar, S. (2007). Zonal co-location pattern discovery with dynamic parameters. In Proceedings of the 7th IEEE International Conference on Data Mining (ICDM) (pp. 433–438). IEEE Press.
5. He, Y., Wang, L., Fang, F., et al. (2018). Discovering congestion propagation patterns by co-location pattern mining. In Proceedings of the Asia Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint Conference on Web and Big Data (APWeb-WAIM)., LNCS 11268 (pp. 46–55). Springer.