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
Spatial Data Mining: A Database Approach
SSD '97 Proceedings of the 5th International Symposium on Advances in Spatial Databases
Mining Association Rules in Multiple Relations
ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
A bibliography of temporal, spatial and spatio-temporal data mining research
ACM SIGKDD Explorations Newsletter
A progressive refinement approach to spatial data mining
A progressive refinement approach to spatial data mining
Hi-index | 0.00 |
In this paper, we are interested in the problem of extracting spatial association rules in Geographic Information Systems (GIS). We propose an algorithm that extends existing methods to deal with spatial and non-spatial data over multiple layers. It handles hierarchical, multi-valued attributes, and produces general spatial association rules. We also present a prototype, which has been applied on a real and large geographic database in the field of mineral exploration.