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2010
Book Article
Title

Spatial data mining in practice

Title Supplement
Principles and case studies
Abstract
Almost any data can be referenced in geographic space. Such data permit advanced analyses that utilize the position and relationships of objects in space as well as geographic background information. Even though spatial data mining is still a young research discipline, in the past years research advances have shown that the particular challenges of spatial data can be mastered and that the technology is ready for practical application when spatial aspects are treated as an integrated part of data mining and model building. In this chapter in particular, we give a detailed description of several customer projects that we have carried out and which all involve customized data mining solutions for business relevant tasks. The applications range from customer segmentation to the prediction of traffic frequencies and the analysis of GPS trajectories. They have been selected to demonstrate key challenges, to provide advanced solutions and to arouse further research questions.
Author(s)
Körner, Christine  
Hecker, Dirk  
Krause-Traudes, Maike  
May, Michael  
Scheider, Simon  
Schulz, Daniel  
Stange, Hendrik  
Wrobel, Stefan  
Mainwork
Data mining for business applications  
DOI
10.24406/publica-r-222791
10.3233/978-1-60750-633-1-164
File(s)
Download (1.27 MB)
Language
English
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS  
Keyword(s)
  • spatial data mining

  • algorithm

  • case study

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