Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
GeoMiner: a system prototype for spatial data mining
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
A spatial data mining method by Delaunay triangulation
GIS '97 Proceedings of the 5th ACM international workshop on Advances in geographic information systems
Mining frequent neighboring class sets in spatial databases
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Using a Hash-Based Method with Transaction Trimming for Mining Association Rules
IEEE Transactions on Knowledge and Data Engineering
A Distribution-Based Clustering Algorithm for Mining in Large Spatial Databases
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Efficient and Effective Clustering Methods for Spatial Data Mining
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Discovery of Spatial Association Rules in Geographic Information Databases
SSD '95 Proceedings of the 4th International Symposium on Advances in Spatial Databases
Mining viewpoint patterns in image databases
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Fast mining of spatial collocations
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
A partial join approach for mining co-location patterns
Proceedings of the 12th annual ACM international workshop on Geographic information systems
Image Database Design Based on 9D-SPA Representation for Spatial Relations
IEEE Transactions on Knowledge and Data Engineering
A Join-Less Approach for Co-Location Pattern Mining: A Summary of Results
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Mining spatial association rules in image databases
Information Sciences: an International Journal
Probabilistic robot navigation in partially observable environments
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Constrained frequent pattern mining on univariate uncertain data
Journal of Systems and Software
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In this paper, we propose a novel algorithm, called 9DSPA-Miner, to mine frequent patterns from an image database, where every image is represented by the 9D-SPA representation. Our proposed method consists of three phases. First, we scan the database once and create an index structure. Next, the index structure is scanned to find all frequent patterns of length two. Finally, we use the frequent k-patterns (k=2) to generate candidate (k+1)-patterns and check if the support of each candidate generated is not less than the user-specified minimum support threshold by using the index structure. Then, the steps in the third phase are repeated until no more frequent patterns can be found. Since the 9DSPA-Miner algorithm uses the characteristics of the 9D-SPA representation to prune most of impossible candidates, the experiment results demonstrate that it is more efficient and scalable than the modified Apriori method.