Efficient Implementation of the Fuzzy c-Means Clustering Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
The X-tree: An Index Structure for High-Dimensional Data
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
A Comparative Study of Spatial Indexing Techniques for Multidimensional Scientific Datasets
SSDBM '04 Proceedings of the 16th International Conference on Scientific and Statistical Database Management
Data Structures and Algorithm Analysis in C++ (3rd Edition)
Data Structures and Algorithm Analysis in C++ (3rd Edition)
Indexing and ranking in Geo-IR systems
Proceedings of the 2005 workshop on Geographic information retrieval
A novel spatial index for case based geographic retrieval
Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
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In spatial databases, traditional approach is to build separate indexing structures for spatial and non-spatial attributes. This article introduces a new coupled approach that combines a 3D spatial primary index and a fuzzy non-spatial secondary index. Based on tests with several types of queries on a meteorological data set, it is shown that our coupled structure reduces the number of iterations and the time consumed for querying compared with the traditional uncoupled one.