EHUCM: An Efficient Algorithm for Mining High Utility Co-location Patterns from Spatial Datasets with Feature-specific Utilities
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-86472-9_17
Reference8 articles.
1. Yang, P., Wang, L., Wang, X., Zhou, L.: SCPM-CR: a novel method for spatial co-location pattern mining with coupling relation consideration. IEEE Trans. Knowl. Data Eng. 4347, 1–14 (2021). https://doi.org/10.1109/TKDE.2021.3060119
2. Yu, W.: Spatial co-location pattern mining for location-based services in road networks. Exp. Syst. Appl. 46, 324–335 (2016). https://doi.org/10.1016/j.eswa.2015.10.010
3. Akbari, M., Samadzadegan, F., Weibel, R.: A generic regional spatio-temporal co-occurrence pattern mining model: a case study for air pollution. J. Geogr. Syst. 17(3), 249–274 (2015). https://doi.org/10.1007/s10109-015-0216-4
4. Yoo, J.S., Bow, M.: A framework for generating condensed co-location sets from spatial databases. Intell. Data Anal. 23, 333–355 (2019). https://doi.org/10.3233/IDA-173752
5. Truong, T., Duong, H., Le, B., Fournier-Viger, P.: Efficient algorithms for mining frequent high utility sequences with constraints. Inf. Sci. (Ny). 568, 239–264 (2021)
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