CURE: an efficient clustering algorithm for large databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Spatial databases with application to GIS
Spatial databases with application to GIS
BIRCH: A New Data Clustering Algorithm and Its Applications
Data Mining and Knowledge Discovery
The cougar approach to in-network query processing in sensor networks
ACM SIGMOD Record
Incremental Clustering for Mining in a Data Warehousing Environment
VLDB '98 Proceedings of the 24rd 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
Spatial Data Mining: A Database Approach
SSD '97 Proceedings of the 5th International Symposium on Advances in Spatial Databases
Efficient Polygon Amalgamation Methods for Spatial OLAP and Spatial Data Mining
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
STING: A Statistical Information Grid Approach to Spatial Data Mining
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
The design of an acquisitional query processor for sensor networks
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
GIS: A Computing Perspective, 2nd Edition
GIS: A Computing Perspective, 2nd Edition
Multiresolution amalgamation: dynamic spatial data cube generation
ADC '04 Proceedings of the 15th Australasian database conference - Volume 27
Supporting spatial aggregation in sensor network databases
Proceedings of the 12th annual ACM international workshop on Geographic information systems
Supporting ranking and clustering as generalized order-by and group-by
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Grouping Results of Queries to Ontological Knowledge Bases by Conceptual Clustering
ICCCI '09 Proceedings of the 1st International Conference on Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems
Query Results Clustering by Extending SPARQL with CLUSTER BY
OTM '09 Proceedings of the Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems: ADI, CAMS, EI2N, ISDE, IWSSA, MONET, OnToContent, ODIS, ORM, OTM Academy, SWWS, SEMELS, Beyond SAWSDL, and COMBEK 2009
Querying streaming point clusters as regions
Proceedings of the ACM SIGSPATIAL International Workshop on GeoStreaming
On a fuzzy group-by and its use for fuzzy association rule mining
ADBIS'10 Proceedings of the 14th east European conference on Advances in databases and information systems
Ways to increase the efficiency of information systems
AIKED'11 Proceedings of the 10th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases
Similarity queries: their conceptual evaluation, transformations, and processing
The VLDB Journal — The International Journal on Very Large Data Bases
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The development of areas such as remote and airborne sensing, location based services, and geosensor networks enables the collection of large volumes of spatial data. These datasets necessitate the wide application of spatial databases. Queries on these geo-referenced data often require the aggregation of isolated data points to form spatial clusters and obtain properties of the clusters. However, current SQL standard does not provide an effective way to form and query spatial clusters. In this paper, we aim at introducing Cluster By into spatial databases to allow a broad range of interesting queries to be posted on spatial clusters. We also provide a language construct to specify spatial clustering algorithms. The extension is demonstrated with several motivating examples.