Towards an effective cooperation of the user and the computer for classification

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Towards an effective cooperation of the user and the computer for classification

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International Conference on Knowledge Discovery and Data Mining archive
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining table of contents

Boston, Massachusetts, United States

Pages: 179 - 188

Year of Publication: 2000

ISBN:1-58113-233-6

Authors

Mihael Ankerst	Institute for Computer Science, University of Munich, Oettingenstr. 67, D-80538 München, Germany
Martin Ester	Institute for Computer Science, University of Munich, Oettingenstr. 67, D-80538 München, Germany
Hans-Peter Kriegel	Institute for Computer Science, University of Munich, Oettingenstr. 67, D-80538 München, Germany

Sponsors

SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
AAAI : Am Assoc for Artifical Intelligence
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGMOD: ACM Special Interest Group on Management of Data

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 5, Downloads (12 Months): 50, Citation Count: 25

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REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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	Charu C. Aggarwal, Towards effective and interpretable data mining by visual interaction, ACM SIGKDD Explorations Newsletter, v.3 n.2, January 2002
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