A new join-less approach for co-location pattern mining

Wang, L; Bao, Y; Lu, J; Yip, YJ

Abstract

With the rapid growth and extensive applications of the spatial dataset, itpsilas getting more important to solve how to find spatial knowledge automatically from spatial datasets. Spatial co-location patterns represent the subsets of features whose instances are frequently located together in geographic space. Itpsilas difficult to discovery co-location patterns because of the huge amount of data brought by the instances of spatial features. A large fraction of the computation time is devoted to generating the table instances of co-location patterns. The essence of co-location patterns discovery and three kinds of co-location patterns mining algorithms proposed in recent years are analyzed, and a new join-less approach for co-location patterns mining, which based on a data structure - CPI-tree (Co-location Pattern Instance Tree), is proposed. The CPI-tree materializes spatial neighbor relationships. All co-location table instances can be generated quickly with a CPI-tree. This paper proves the correctness and completeness of the new approach. Finally, an experimental evaluation using synthetic datasets and a real world dataset shows that the algorithm is computationally more efficient than the join-less algorithm

Citation

Wang, L., Bao, Y., Lu, J., & Yip, Y. (2008, January). A new join-less approach for co-location pattern mining. Presented at 8th IEEE International Conference on Computer and Information Technology, Sydney, NSW

• Presentation Conference Type: Other
• Conference Name: 8th IEEE International Conference on Computer and Information Technology
• Conference Location: Sydney, NSW
• Start Date: Jan 1, 2008
• Publication Date: Jul 1, 2008
• Deposit Date: Aug 14, 2012
• Publisher URL: http://dx.doi.org/10.1109/CIT.2008.4594673
• Additional Information: Additional Information : Paper from the 8th IEEE International Conference on Computer and Information Technology, 2008. CIT 2008. Sydney, NSW, 2008; Event Type : Conference