Semi-Automatic Visual Subgroup Mining using VIKAMINE.
M. Atzmüller, und F. Puppe.
Journal of Universal Computer Science 11 (11): 1752-1765 (2005)

Visual mining methods enable the direct integration of the user to overcome major problems of automatic data mining methods, e.g., the presentation of uninteresting results, lack of acceptance of the discovered findings, or limited confidence in these. We present a novel subgroup mining approach for explorative and descriptive data mining implemented in the VIKAMINE system. We propose several integrated visualization methods to support subgroup mining. Furthermore, we describe three case studies using data from fielded systems in the medical domain.

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http://www.jucs.org/jucs_11_11/semi_automatic_visual_subgroup

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@article{atzmueller2005semiautomatic,
  abstract = {Visual mining methods enable the direct integration of the user to overcome major problems of automatic data mining methods, e.g., the presentation of uninteresting results, lack of acceptance of the discovered findings, or limited confidence in these. We present a novel subgroup mining approach for explorative and descriptive data mining implemented in the VIKAMINE system. We propose several integrated visualization methods to support subgroup mining. Furthermore, we describe three case studies using data from fielded systems in the medical domain.},
  added-at = {2009-04-14T17:32:17.000+0200},
  author = {Atzmüller, Martin and Puppe, Frank},
  biburl = {https://puma.uni-kassel.de/bibtex/2441e7f60d02f2fd1ec0eb913545a4c89/jaeschke},
  date = {2006-04-19},
  description = {dblp},
  doi = {10.3217/jucs-011-11-1752},
  interhash = {0b67dd9c2f5aacb51b76de3e2b9a2116},
  intrahash = {441e7f60d02f2fd1ec0eb913545a4c89},
  journal = {Journal of Universal Computer Science},
  keywords = {classification discovery subgroup vikamine},
  number = 11,
  pages = {1752-1765},
  timestamp = {2009-04-14T17:32:17.000+0200},
  title = {Semi-Automatic Visual Subgroup Mining using VIKAMINE.},
  url = {http://www.jucs.org/jucs_11_11/semi_automatic_visual_subgroup},
  volume = 11,
  year = 2005
}

%0 Journal Article
%1 atzmueller2005semiautomatic
%A Atzmüller, Martin
%A Puppe, Frank
%D 2005
%J Journal of Universal Computer Science
%K classification discovery subgroup vikamine
%N 11
%P 1752-1765
%R 10.3217/jucs-011-11-1752
%T Semi-Automatic Visual Subgroup Mining using VIKAMINE.
%U http://www.jucs.org/jucs_11_11/semi_automatic_visual_subgroup
%V 11
%X Visual mining methods enable the direct integration of the user to overcome major problems of automatic data mining methods, e.g., the presentation of uninteresting results, lack of acceptance of the discovered findings, or limited confidence in these. We present a novel subgroup mining approach for explorative and descriptive data mining implemented in the VIKAMINE system. We propose several integrated visualization methods to support subgroup mining. Furthermore, we describe three case studies using data from fielded systems in the medical domain.

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Semi-Automatic Visual Subgroup Mining using VIKAMINE.
M. Atzmüller, und F. Puppe.
Journal of Universal Computer Science 11 (11): 1752-1765 (2005)

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Semi-Automatic Visual Subgroup Mining using VIKAMINE.M. Atzmüller, und F. Puppe. Journal of Universal Computer Science 11 (11): 1752-1765 (2005)

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Semi-Automatic Visual Subgroup Mining using VIKAMINE.
M. Atzmüller, und F. Puppe.
Journal of Universal Computer Science 11 (11): 1752-1765 (2005)