Visual data mining in large geospatial point sets

@article{Keim2004VisualDM,
  title={Visual data mining in large geospatial point sets},
  author={Daniel A. Keim and Christian Panse and Mike Sips and Stephen C. North},
  journal={IEEE Computer Graphics and Applications},
  year={2004},
  volume={24},
  pages={36-44}
}
Visual data-mining techniques have proven valuable in exploratory data analysis, and they have strong potential in the exploration of large databases. Detecting interesting local patterns in large data sets is a key research challenge. Particularly challenging today is finding and deploying efficient and scalable visualization strategies for exploring large geospatial data sets. One way is to share ideas from the statistics and machine-learning disciplines with ideas and methods from the… CONTINUE READING
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