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» A relational perspective on spatial data mining
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DATAMINE
2000
118views more  DATAMINE 2000»
13 years 7 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...
PKDD
2004
Springer
141views Data Mining» more  PKDD 2004»
14 years 24 days ago
Spatial Associative Classification at Different Levels of Granularity: A Probabilistic Approach
In this paper we propose a novel spatial associative classifier method based on a multi-relational approach that takes spatial relations into account. Classification is driven by s...
Michelangelo Ceci, Annalisa Appice, Donato Malerba
GEOINFORMATICA
2006
102views more  GEOINFORMATICA 2006»
13 years 7 months ago
Mining Co-Location Patterns with Rare Events from Spatial Data Sets
Abstract A co-location pattern is a group of spatial features/events that are frequently co-located in the same region. For example, human cases of West Nile Virus often occur in r...
Yan Huang, Jian Pei, Hui Xiong
ICDM
2009
IEEE
113views Data Mining» more  ICDM 2009»
14 years 2 months ago
Spatiotemporal Relational Random Forests
Abstract—We introduce and validate Spatiotemporal Relational Random Forests, which are random forests created with spatiotemporal relational probability trees. We build on the do...
Timothy A. Supinie, Amy McGovern, John Williams, J...
KDD
2006
ACM
112views Data Mining» more  KDD 2006»
14 years 7 months ago
K-means clustering versus validation measures: a data distribution perspective
K-means is a widely used partitional clustering method. While there are considerable research efforts to characterize the key features of K-means clustering, further investigation...
Hui Xiong, Junjie Wu, Jian Chen