An Algorithm of Constrained Spatial Association Rules Based on Binary

Authors:
Gang Fang;Zukuan Wei;Qian Yin
Affiliations:
School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China 610054;School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China 610054;College of Information Science and Technology, Beijing Normal University, Beijing, China 100875
Venue:
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II
Year:
2008

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Abstract

An algorithm of constrained association rules mining was presented in order to search for some items expected by people. Since some presented algorithms of association rules mining based on binary are complicated to generate frequent candidate itemsets, they may pay out heavy cost when these algorithms are used to extract constrained spatial association rules. And so this paper proposes an algorithm of constrained spatial association rules based on binary, the algorithm is suitable for mining constrained association among some different spatial objects under the same spatial pattern, which uses the way of ascending value to generates frequent candidate itemsets and digital character to reduce the number of scanned transaction in order to improve the efficiency. The experiment indicates that the algorithm is faster and more efficient than theses presented algorithms based on binary when mining constrained spatial association rules from spatial database.