Spatial Data Mining in Practice: Principles and Case Studies

Authors:
Christine Körner;Dirk Hecker;Maike Krause-Traudes;Michael May;Simon Scheider;Daniel Schulz;Hendrik Stange;Stefan Wrobel
Affiliations:
Fraunhofer IAIS, Sankt Augustin, Germany;Fraunhofer IAIS, Sankt Augustin, Germany;Fraunhofer IAIS, Sankt Augustin, Germany;Fraunhofer IAIS, Sankt Augustin, Germany;Fraunhofer IAIS, Sankt Augustin, Germany;Fraunhofer IAIS, Sankt Augustin, Germany;Fraunhofer IAIS, Sankt Augustin, Germany;Fraunhofer IAIS, Sankt Augustin, Germany and Department of Computer Science III, University of Bonn, Germany
Venue:
Proceedings of the 2010 conference on Data Mining for Business Applications
Year:
2010

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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.