Applications of spatial data structures: Computer graphics, image processing, and GIS
Applications of spatial data structures: Computer graphics, image processing, and GIS
The nature of statistical learning theory
The nature of statistical learning theory
Density-Based Clustering in Spatial Databases: The Algorithm GDBSCAN and Its Applications
Data Mining and Knowledge Discovery
An Algorithm for Multi-relational Discovery of Subgroups
PKDD '97 Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery
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
Discovery of Spatial Association Rules in Geographic Information Databases
SSD '95 Proceedings of the 4th International Symposium on Advances in Spatial Databases
CrossMine: Efficient Classification Across Multiple Database Relations
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Inducing Multi-Level Association Rules from Multiple Relations
Machine Learning
Why collective inference improves relational classification
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining changing regions from access-constrained snapshots: a cluster-embedded decision tree approach
Journal of Intelligent Information Systems
Discovery of spatial association rules in geo-referenced census data: A relational mining approach
Intelligent Data Analysis
Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)
Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)
Discovering Emerging Patterns in Spatial Databases: A Multi-relational Approach
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
A Method for Multi-relational Classification Using Single and Multi-feature Aggregation Functions
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
A multi-relational approach to spatial classification
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Transductive learning for spatial regression with co-training
Proceedings of the 2010 ACM Symposium on Applied Computing
Semi-Supervised Learning
Summarization for geographically distributed data streams
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part III
Mining model trees from spatial data
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
Mining and filtering multi-level spatial association rules with ARES
ISMIS'05 Proceedings of the 15th international conference on Foundations of Intelligent Systems
Spatial contextual classification and prediction models for mining geospatial data
IEEE Transactions on Multimedia
| Hi-index | 0.00 |
The rapid growth in the amount of spatial data available in Geographical Information Systems has given rise to substantial demand of data mining tools which can help uncover interesting spatial patterns. We advocate the relational mining approach to spatial domains, due to both various forms of spatial correlation which characterize these domains and the need to handle spatial relationships in a systematic way. We present some major achievements in this research direction and point out some open problems.