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2005
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A Join-Less Approach for Co-Location Pattern Mining: A Summary of Results

9 years 5 months ago
A Join-Less Approach for Co-Location Pattern Mining: A Summary of Results
Spatial co-location patterns represent the subsets of features whose instances are frequently located together in geographic space. Co-location pattern discovery presents challenges since the instances of spatial features are embedded in a continuous space and share a variety of spatial relationships. A large fraction of the computation time is devoted to identifying the instances of co-location patterns. We propose a novel join-less approach for co-location pattern mining, which materializes spatial neighbor relationships with no loss of co-location instances and reduces the computational cost of identifying the instances. The joinless co-location mining algorithm is efficient since it uses an instance-lookup scheme instead of an expensive spatial or instance join operation for identifying co-location instances. We prove the join-less algorithm is correct and complete in finding co-location rules. The experimental evaluations using synthetic datasets and real world datasets show th...
Jin Soung Yoo, Shashi Shekhar, Mete Celik
Added 24 Jun 2010
Updated 24 Jun 2010
Type Conference
Year 2005
Where ICDM
Authors Jin Soung Yoo, Shashi Shekhar, Mete Celik
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