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» Using Formal Ontology for Integrated Spatial Data Mining
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CINQ
2004
Springer
225views Database» more  CINQ 2004»
15 years 3 months ago
A Data Mining Query Language for Knowledge Discovery in a Geographical Information System
Spatial data mining is a process used to discover interesting but not explicitly available, highly usable patterns embedded in both spatial and nonspatial data, which are possibly ...
Donato Malerba, Annalisa Appice, Michelangelo Ceci
64
Voted
PKDD
2001
Springer
104views Data Mining» more  PKDD 2001»
15 years 2 months ago
Data Reduction Using Multiple Models Integration
Large amount of available information does not necessarily imply that induction algorithms must use all this information. Samples often provide the same accuracy with less computat...
Aleksandar Lazarevic, Zoran Obradovic
ICDM
2006
IEEE
127views Data Mining» more  ICDM 2006»
15 years 3 months ago
Predictive Integration of Gene Ontology-Driven Similarity and Functional Interactions
There is a need to develop methods to automatically incorporate prior knowledge to support the prediction and validation of novel functional associations. One such important sourc...
Francisco Azuaje, Haiying Wang, Huiru Zheng, Olivi...
TGIS
2002
175views more  TGIS 2002»
14 years 9 months ago
Using Ontologies for Integrated Geographic Information Systems
Today, there is a huge amount of data gathered about the Earth, not only from new spatial information systems, but also from new and more sophisticated data collection technologie...
Frederico T. Fonseca, Max J. Egenhofer, Peggy Agou...
DATAMINE
2000
118views more  DATAMINE 2000»
14 years 9 months ago
Spatial Data Mining: Database Primitives, Algorithms and Efficient DBMS Support
Abstract: Spatial data mining algorithms heavily depend on the efficient processing of neighborhood relations since the neighbors of many objects have to be investigated in a singl...
Martin Ester, Alexander Frommelt, Hans-Peter Krieg...