References
- Adilmagambetov, A., Zaiane, O.R. and Osornio-Vargas, A. (2013). Discovering co-location patterns in datasets with extended spatial objects, International Conference on Data Warehousing and Knowledge Discovery, Berlin, Germany, pp. 84-96.
- Agrawal, R. and Srikant, R. (1994). Fast algorithms for mining association rules, 20th International Conference Very Large Data Bases, VLDB, Santiago de Chile, Chile, pp. 487-499.
- Appice, A., Berardi, M., Ceci, M. and Malerba, D. (2005). Mining and filtering multi-level spatial association rules with ares, International Symposium on Methodologies for Intelligent Systems, Saratoga Springs, NY, USA, pp. 342-353.
- Barua, S. and Sander, J. (2011). SSCP: Mining statistically significant co-location patterns, International Symposium on Spatial and Temporal Databases, Minneapolis, MN, USA, pp. 2-20.
- Bembenik, R., Ruszczyk, A. and Protaziuk, G. (2014). Discovering collocation rules and spatial association rules in spatial data with extended objects using Delaunay diagrams, International Conference on Rough Sets and Intelligent Systems Paradigms, Granada/Madrid, Spain, pp. 293-300.
- Bembenik, R. and Rybi´nski, H. (2009). FARICS: A method of mining spatial association rules and collocations using clustering and Delaunay diagrams, Journal of Intelligent Information Systems 33(1): 41-64.10.1007/s10844-008-0076-1
- Fayyad, U., Piatetsky-Shapiro, G. and Smyth, P. (1996). From data mining to knowledge discovery in databases, AI Magazine 17(3): 37.
- Karamshuk, D., Noulas, A., Scellato, S., Nicosia, V. and Mascolo, C. (2013). Geo-spotting: Mining online location-based services for optimal retail store placement, 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Chicago, IL, USA, pp. 793-801.
- Kim, S.K., Lee, J.H., Ryu, K.H. and Kim, U. (2014). A framework of spatial co-location pattern mining for ubiquitous GIS, Multimedia Tools and Applications 71(1): 199-218.
- Koperski, K. and Han, J. (1995). Discovery of spatial association rules in geographic information databases, in M.J. Egenhofer and J.R. Herring (Eds.), Advances in Spatial Databases, Springer, Berlin/Heidelberg, pp. 47-66.
- Li, D.,Wang, S. and Li, D. (2016). Spatial Data Mining: Theory and Application, Springer, Berlin/Heidelberg.
- Li, J., Zaïane, O.R. and Osornio-Vargas, A. (2014). Discovering statistically significant co-location rules in datasets with extended spatial objects, International Conference on Data Warehousing and Knowledge Discovery, Munich, Germany, pp. 124-135.
- Lisi, F. A. and Malerba, D. (2004). Inducing multi-level association rules from multiple relations, Machine Learning 55(2): 175-210.10.1023/B:MACH.0000023151.65011.a3
- Loglisci, C., Ceci, M. and Malerba, D. (2010). Relational learning of disjunctive patterns in spatial networks, 1st Workshop on Dynamic Networks and Knowledge Discovery, Barcelona, Spain, pp. 17-28.
- Okabe, A., Boots, B., Sugihara, K. and Chiu, S.N. (2009). Spatial Tessellations: Concepts and Applications of Voronoi Diagrams, John Wiley & Sons, Chichester. Oracle (2017). Oracle Spatial Developer’s Guide, https://docs.oracle.com/cd/B28359_01/appdev.111/b28400/sdo_objgeom.htm#SPATL120.
- PostGIS (2017). Buffer operation in PostGIS, http://www.postgis.net/docs/ST_Buffer.html.
- Rineau, L. (2017). 2D conforming triangulations and meshes. CGAL user and reference manual, https://doc.cgal.org/latest/Mesh_2/index.html.
- Shekhar, S. and Huang, Y. (2001). Discovering spatial co-location patterns: A summary of results, International Symposium on Spatial and Temporal Databases, Redondo Beach, CA, USA, pp. 236-256.
- Shekhar, S. and Xiong, H. (2007). Encyclopedia of GIS, Springer Science & Business Media, New York, NY.
- Xiong, H., Shekhar, S., Huang, Y., Kumar, V., Ma, X. and Yoo, J. S. (2004). A framework for discovering co-location patterns in data sets with extended spatial objects, 4th SIAM International Conference on Data Mining, Lake Buena Vista, FL, USA, pp. 78-89.
- Yang, X. and Cui, W. (2008). A novel spatial clustering algorithm based on Delaunay triangulation, International Conference on Earth Observation Data Processing and Analysis, Wuhan, China, pp. 728530-728530.
- Zheng, Y., Capra, L., Wolfson, O. and Yang, H. (2014). Urban computing: Concepts, methodologies, and applications, ACM Transactions on Intelligent Systems and Technology 5(3): 38.