An order-clique-based approach for mining maximal co-locations

Wang, L; Zhou, L; Lu, J; Yip, YJ

Abstract

Most algorithms for mining spatial co-locations adopt an Apriori-like approach to generate size-k prevalence co-locations after size-(k − 1) prevalence co-locations. However, generating and storing the co-locations and table instances is costly. A novel order-clique-based approach for mining maximal co-locations is proposed in this paper. The efficiency of the approach is achieved by two techniques: (1) the spatial neighbor relationships and the size-2 prevalence co-locations are compressed into extended prefix-tree structures, which allows the order-clique-based approach to mine candidate maximal co-locations and co-location instances; and (2) the co-location instances do not need to be stored after computing some characteristics of the corresponding co-location, which significantly reduces the execution time and space required for mining maximal co-locations. The performance study shows that the new method is efficient for mining both long and short co-location patterns, and is faster than some other methods (in particular the join-based method and the join-less method).

Citation

Wang, L., Zhou, L., Lu, J., & Yip, Y. (2009). An order-clique-based approach for mining maximal co-locations. Information Sciences, 179(19), 3370-3382. https://doi.org/10.1016/j.ins.2009.05.023

• Journal Article Type: Article
• Publication Date: Jan 1, 2009
• Deposit Date: Aug 29, 2012
• Journal: Information Sciences
• Print ISSN: 0020-0255
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 179
• Issue: 19
• Pages: 3370-3382
• DOI: https://doi.org/10.1016/j.ins.2009.05.023
• Publisher URL: http://dx.doi.org/10.1016/j.ins.2009.05.023