MPCD: An Algorithm for Discovering Multilevel Prevalent Co-location Patterns from Heterogeneous Distribution of Spatial Datasets

Author:

Tran VanhaORCID,Bui Thiloan,Le Hoangan

Publisher

Springer Nature Switzerland

Reference23 articles.

1. Bao, X., Wang, L.: A clique-based approach for co-location pattern mining. Inf. Sci. 490, 244–264 (2019)

2. Debnath, M., Tripathi, P.K., Elmasri, R.: K-dbscan: identifying spatial clusters with differing density levels. In: DMIA, pp. 51–60. IEEE (2015)

3. Deng, M., Cai, J., Liu, Q., He, Z., Tang, J.: Multi-level method for discovery of regional co-location patterns. Int. J. Geogr. Inf. Sci. 31(9), 1846–1870 (2017)

4. Eppstein, D., Löffler, M., Strash, D.: Listing all maximal cliques in large sparse real-world graphs. J. Exp. Algorithm. 18, 3 (2013)

5. Ester, M., Kriegel, H.P., Sander, J.: A density-based algorithm for discovering clusters in large spatial databases with noise. In: KDD, vol. 96, pp. 226–231 (1996)

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