Spatial Subgroup Mining Integrated in an Object-Relational Spatial Database
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
Evolutionary Hot Spots Data Mining - An Architecture for Exploring for Interesting Discoveries
PAKDD '99 Proceedings of the Third Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining
Discovery of Spatial Association Rules in Geographic Information Databases
SSD '95 Proceedings of the 4th International Symposium on Advances in Spatial Databases
Discovering Spatial Co-location Patterns: A Summary of Results
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
STING: A Statistical Information Grid Approach to Spatial Data Mining
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Supervised Clustering " Algorithms and Benefits
ICTAI '04 Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence
Using supervised clustering to enhance classifiers
ISMIS'05 Proceedings of the 15th international conference on Foundations of Intelligent Systems
On supervised density estimation techniques and their application to spatial data mining
Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems
Finding regional co-location patterns for sets of continuous variables in spatial datasets
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
Regional Pattern Discovery in Geo-referenced Datasets Using PCA
MLDM '09 Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition
A Framework for Multi-Objective Clustering and Its Application to Co-Location Mining
ADMA '09 Proceedings of the 5th International Conference on Advanced Data Mining and Applications
REG^2: a regional regression framework for geo-referenced datasets
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Towards region discovery in spatial datasets
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
Analyzing change in spatial data by utilizing polygon models
Proceedings of the 1st International Conference and Exhibition on Computing for Geospatial Research & Application
A classification algorithm based on local cluster centers with a few labeled training examples
Knowledge-Based Systems
Analyzing the composition of cities using spatial clustering
Proceedings of the 2nd ACM SIGKDD International Workshop on Urban Computing
A Framework for Discriminative Polygonal Place Scoping
Proceedings of The First ACM SIGSPATIAL International Workshop on Computational Models of Place
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The discovery of interesting regions in spatial datasets is an important data mining task. In particular, we are interested in identifying disjoint, contiguous regions that are unusual with respect to the distribution of a given class; i.e. a region that contains an unusually low or high number of instances of a particular class. This paper centers on the discussion of techniques, methodologies, and algorithms to discover such regions. A measure of interestingness and a supervised clustering framework are introduced for this purpose. Moreover, three supervised clustering algorithms are proposed in the paper: an agglomerative hierarchical supervised clustering named SCAH, an agglomerative, grid-based clustering method named SCHG, and lastly an algorithm named SCMRG which searches a multi-resolution grid structure top down for interesting regions. Finally, experimental results of applying the proposed framework and algorithms to the problem of identifying hotspots in spatial datasets are discussed.