An algorithm of mining spatial topology association rules based on Apriori

Abstract

This paper introduces an algorithm of mining spatial topology association rules based on Apriori, which is used to mining spatial multilayer transverse association rules from spatial database. This algorithm creates candidate frequent topological itemsets via down-top search strategy as Apriori, which is suitable for mining short spatial topological frequent itemsets. This algorithm compresses a kind of spatial topological relation to form a digit. By this method, firstly, the algorithm may efficiently reduce some storage space when creating mining database. Secondly, the algorithm is easy to computing topological relation between spatial objects, namely, it may fast compute support of candidate itemsets. Finally, the algorithm is fast to connect (k+1)-candidate itemsets of k-frequent itemsets as down-top search strategy. The result of experiment indicates that the algorithm of mining spatial topology association rules based on Apriori is able to extract spatial multilayer transverse association rules from spatial database via efficient data store, and it is very efficient to extract short frequent topology association rules.