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2004
ACM

A partial join approach for mining co-location patterns

11 years 5 months ago
A partial join approach for mining co-location patterns
Spatial co-location patterns represent the subsets of events whose instances are frequently located together in geographic space. We identified the computational bottleneck in the execution time of a current co-location mining algorithm. A large fraction of the join-based co-location miner algorithm is devoted to computing joins to identify instances of candidate co-location patterns. We propose a novel partialjoin approach for mining co-location patterns efficiently. It transactionizes continuous spatial data while keeping track of the spatial information not modeled by transactions. It uses a transaction-based Apriori algorithm as a building block and adopts the instance join method for residual instances not identified in transactions. We show that the algorithm is correct and complete in finding all co-location rules which have prevalence and conditional probability above the given thresholds. An experimental evaluation using synthetic datasets and a real dataset shows that our al...
Jin Soung Yoo, Shashi Shekhar
Added 11 Nov 2009
Updated 11 Nov 2009
Type Conference
Year 2004
Where GIS
Authors Jin Soung Yoo, Shashi Shekhar
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