Synonyms
Mining collocation patterns; Mining spatial association patterns; Co-occurrence; Association; Participation ratio; Participation index; Reference‐feature centric
Definition
A spatial co-location pattern associates the co-existence of a set of non-spatial features in a spatial neighborhood. For example, a co-location pattern can associate contaminated water reservoirs with a certain disease within 5 km distance from them. For a concrete definition of the problem, consider number n of spatial datasets R 1, R 2, …, R n , such that each R i contains objects that have a common non-spatial feature f i . For instance, R 1 may store locations of water sources, R 2 may store locations of appearing disease symptoms, etc. Given a distance threshold ε, two objects on the map (independent of their feature labels) are neighbors if their distance is at most ε. We can define a co-location pattern Pby an undirected connected graph where each node corresponds to a feature and each edge...
This is a preview of subscription content, log in via an institution to check access.
Recommended Reading
Agrawal, R., Skrikant, R.: Fast algorithms for mining association rules. In: Proc. of the 20th Int. Conf. on Very Large Data Bases, pp. 487–499 (1994)
Brinkhoff, T., Kriegel, H.P., Seeger, B.: Efficient processing of spatial joins using r-trees. In: Proc. of ACM SIGMOD Int'l Conference (1993)
Huang, Y., Xiong, H., Shekhar, S., Pei, J.: Mining confident co-location rules without a support threshold. In: Proc. of the 18th ACM Symposium on Applied Computing (ACM SAC) (2003)
Koperski, K., Han, J.: Discovery of spatial association rules in geographic information databases. In: Proc. of the 4th Int. Symp. Advances in Spatial Databases, SSD, vol. 951, pp. 47–66 (1995)
Mamoulis, N., Papadias, D.: Multiway spatial joins. ACM Trans. Database Syst. 26(4), pp. 424–475 (2001)
Morimoto, Y.: Mining frequent neighboring class sets in spatial databases. In Proc. of ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining. (2001)
Munro, R., Chawla, S., Sun, P.: Complex spatial relationships. In: Proc. of the 3rd IEEE International Conference on Data Mining (ICDM) (2003)
Preparata, F.P., Shamos, M.I.: Computational geometry: an introduction. Springer-Verlag New York, Inc. (1985)
Salmenkivi, M.: Evaluating attraction in spatial point patterns with an application in the field of cultural history. In: Proceedings of the 4th IEEE International Conference on Data Mining. (2004)
Shekhar, S., Huang, Y.: Discovering spatial co-location patterns: A summary of results. In: Proc of the 7th International Symposium on Advances in Spatial and Temporal Databases (SSTD). (2001)
Wang, J., Hsu, W., Lee, M.L.: A framework for mining topological patterns in spatio‐temporal databases. In: Proceedings of the 14th ACM international conference on Information and knowledge management. Full paper in IEEE Trans. KDE, 16(12), 2004. (2005)
Yang, H.: Srinivasan Parthasarathy, and Sameep Mehta. Mining spatial object associations for scientific data. In: Proceedings of the 19th International Joint Conference on Artificial Intelligence (2005)
Zaki, M.J., Gouda, K.: Fast vertical mining using diffsets. In: Proc. of ACM SIGKDD Conference (2003)
Zhang, X., Mamoulis, N., Cheung, D.W.L., Shou, Y.: Fast mining of spatial collocations. In: Proc. of ACM SIGKDD Conference. (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag
About this entry
Cite this entry
Mamoulis, N. (2008). Co-location Patterns, Algorithms. In: Shekhar, S., Xiong, H. (eds) Encyclopedia of GIS. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-35973-1_152
Download citation
DOI: https://doi.org/10.1007/978-0-387-35973-1_152
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-30858-6
Online ISBN: 978-0-387-35973-1
eBook Packages: Computer ScienceReference Module Computer Science and Engineering