The aim of this work is to survey and reflect on the various ways visualization and data mining can be integrated to achieve effective knowledge discovery by involving the best of human and machine capabilities. Following a bottom-up bibliographic research approach, the article categorizes the observed techniques in classes, highlighting current trends, gaps, and potential future directions for research.

Daniel A. Keim and Florian Mansmann and Daniela Oelke and Hartmut Ziegler, Visual Analytics: Combining Automated Discovery with Interactive Visualizations, 2008, Discovery Science,pp. 2-14, ISBN 978-3-540-88410-1., [download], [bibtex]

@inproceedings{Keim-5,
  author = {Daniel A. Keim and Florian Mansmann and Daniela Oelke and Hartmut Ziegler},
  title = {Visual Analytics: Combining Automated Discovery with Interactive Visualizations},
  month = {December},
  year = {2008},
  note = {Discovery Science,pp. 2-14, ISBN 978-3-540-88410-1.},
}