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 00200255Metadata only available from this repository.
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).
|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 > High-Performance Intelligent Computing
?? tserg ??
School of Computing and Engineering > High-Performance Intelligent Computing > Information and Systems Engineering Group
|Depositing User:||Cherry Edmunds|
|Date Deposited:||10 Dec 2012 11:23|
|Last Modified:||10 Dec 2012 11:23|
Downloads per month over past year
Repository Staff Only: item control page