Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Computational geometry in C
Finding Aggregate Proximity Relationships and Commonalities in Spatial Data Mining
IEEE Transactions on Knowledge and Data Engineering
Supporting Data Mining of Large Databases by Visual Feedback Queries
Proceedings of the Tenth International Conference on Data Engineering
An Interval Classifier for Database Mining Applications
VLDB '92 Proceedings of the 18th International Conference on Very Large Data Bases
Knowledge Discovery in Databases: An Attribute-Oriented Approach
VLDB '92 Proceedings of the 18th International Conference on Very Large Data Bases
Efficient and Effective Clustering Methods for Spatial Data Mining
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
SSD '95 Proceedings of the 4th International Symposium on Advances in Spatial Databases
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This paper describes a new approach to knowledge discovery among spatial objects-namely that of partial boundary shape matching. Our focus is on mining spatial data, whereby many objects called features (represented as polygons) are compared with one or more point sets called clusters. The research described has practical application in such domains as Geographic Information Systems, in which a cluster of points (possibly created by an SQL query) is compared to many natural or man-made features to detect partial or total matches of the facing boundaries of the cluster and feature. We begin by using an alpha-shape to characterize the shape of an arbitrary cluster of points, thus producing a set of edges denoting the cluster's boundary. We then provide an approach for detecting a boundary shape match between the facing curves of the cluster and feature, and show how to quantify the value of the match. Optimizations and experimental results are also provided. Finally, we describe several orientation strategies yielding signifficant performance enhancements.