KNIME: The Konstanz Information Miner (original) (raw)

Abstract

The Konstanz Information Miner is a modular environment, which enables easy visual assembly and interactive execution of a data pipeline. It is designed as a teaching, research and collaboration platform, which enables simple integration of new algorithms and tools as well as data manipulation or visualization methods in the form of new modules or nodes. In this paper we describe some of the design aspects of the underlying architecture and briefly sketch how new nodes can be incorporated.

Preview

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

• INFORSENSE LTD.: InforSense KDE. http://www.inforsense.com/kde.html.
• INSIGHTFUL CORPORATION: Insightful Miner. http://www.insightful.com/products/iminer/default.asp.
• SCITEGIC: Pipeline Pilot. http://www.scitegic.com/products/overview/.
• ECLIPSE FOUNDATION (2007):Eclipse 3.2 Documentation. http://www.eclipse.org.
• GILBERT, D. (2005): JFreeChart Developer Guide. Object Refinery Limited, Berkeley, Cal-ifornia. http://www.jfree.org/jfreechart.
• R DEVELOPMENT CORE TEAM (2007): R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0. http://www.R-project.org.
• SIEB C., MEINL T., and BERTHOLD, M. R. (2007): Parallel and distributed data pipelining with KNIME. Mediterranean Journal of Computers and Networks, Special Issue on Data Mining Applications on Supercomputing and Grid Environments. To appear.
  Google Scholar
• WITTEN, I. H. and FRANK, E (2005): Data Mining: Practical ma-chine learning tools and techniques. Morgan Kaufmann, San Francisco. http://www.cs.waikato.ac.nz/˜ml/weka/index.html.

Download references

Author information

Authors and Affiliations

1. ALTANA Chair for Bioinformatics and Information Mining, Department of Computer and Information Science, University of Konstanz, Box M712, 78457, Konstanz, Germany
   Michael R. Berthold, Nicolas Cebron, Fabian Dill, Thomas R. Gabriel, Tobias Kötter, Thorsten Meinl, Peter Ohl, Christoph Sieb, Kilian Thiel & Bernd Wiswedel

Authors

1. Michael R. Berthold
   You can also search for this author inPubMed Google Scholar
2. Nicolas Cebron
   You can also search for this author inPubMed Google Scholar
3. Fabian Dill
   You can also search for this author inPubMed Google Scholar
4. Thomas R. Gabriel
   You can also search for this author inPubMed Google Scholar
5. Tobias Kötter
   You can also search for this author inPubMed Google Scholar
6. Thorsten Meinl
   You can also search for this author inPubMed Google Scholar
7. Peter Ohl
   You can also search for this author inPubMed Google Scholar
8. Christoph Sieb
   You can also search for this author inPubMed Google Scholar
9. Kilian Thiel
   You can also search for this author inPubMed Google Scholar
10. Bernd Wiswedel
    You can also search for this author inPubMed Google Scholar

Editor information

Editors and Affiliations

1. Institute of Computer Science and Institute of Business Economics and Information Systems, University of Hildesheim, Marienburgerplatz 22, 31141, Hildesheim, Germany
   Christine Preisach
2. Lehrstuhl für Mustererkennung und Bildverarbeitung, Universität Freiburg, Gebäude 052, 79110, Freiburg i. Br, Germany
   Hans Burkhardt
3. Institute of Computer Science and Institute of Business Economics and Information Systems, Marienburgerplatz 22, 31141, Hildesheim, Germany
   Lars Schmidt-Thieme
4. Fakultät für Wirtschaftswissenschaften, Lehrstuhl für Betriebswirtschaftslehre, insbes. Marketing, Universitätsstraße 25, 33615, Bielefeld, Germany
   Reinhold Decker

Rights and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Berthold, M.R. et al. (2008). KNIME: The Konstanz Information Miner. In: Preisach, C., Burkhardt, H., Schmidt-Thieme, L., Decker, R. (eds) Data Analysis, Machine Learning and Applications. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78246-9\_38

Download citation

• .RIS
• .ENW
• .BIB
• DOI: https://doi.org/10.1007/978-3-540-78246-9\_38
• Publisher Name: Springer, Berlin, Heidelberg
• Print ISBN: 978-3-540-78239-1
• Online ISBN: 978-3-540-78246-9
• eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)

Publish with us