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

Wang, Lizhen, Zhou, Lihua, Lu, Joan and Yip, Yau Jim (2009) An order-clique-based approach for mining maximal co-locations. Information Sciences, 179 (19). pp. 3370-3382. ISSN 00200255

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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).

Item Type: Article
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Schools: School of Computing and Engineering
School of Computing and Engineering > Diagnostic Engineering Research Centre
School of Computing and Engineering > Diagnostic Engineering Research Centre > Measurement System and Signal Processing Research Group
School of Computing and Engineering > Informatics Research Group
School of Computing and Engineering > Informatics Research Group > Software Engineering Research Group
School of Computing and Engineering > Informatics Research Group > XML, Database and Information Retrieval Research Group
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Depositing User: Cherry Edmunds
Date Deposited: 10 Dec 2012 11:23
Last Modified: 10 Dec 2012 11:23
URI: http://eprints.hud.ac.uk/id/eprint/16247

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