An order-clique-based approach for mining maximal co-locations |
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Authors: | Lizhen Wang Lihua Zhou Jim Yip |
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Affiliation: | a Department of Computer Science and Engineering, School of Information Science and Engineering, Yunnan University, Kunming 650091, China b Department of Informatics, School of Computing and Engineering, University of Huddersfield, Huddersfield HD1 3DH, UK |
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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). |
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Keywords: | Spatial data mining Co-location patterns mining Maximal ordered co-locations Table instances Order-clique-based approach |
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