EXPLORATIVE ASSOCIATION MINING - Cross-sector Knowledge for the European Home Textile Industry

Jessica Huster, Michael Spenke, Gerrit Bury

2008

Abstract

The European home-textile industry lacks cross-sector knowledge and knowledge about its end consumers. Click and ordering data reflect the consuming behaviour as well as the preferences and their changes. They are therefore an important trend indicator, which is not harnessed up to now by this industry sector. In this paper, we report on the solution of the Trend Analyser association mining component that helps designers and product developers to better understand their end consumers. Our component uses explorative data mining to perform a market basket analysis and identify interesting associations. Such associations can help decision makers to understand and study the consuming behaviour and identify early changes in their preferences in order to perform a better production planning.

References

  1. Becks, A., Huster J., (2007). Trend Analysis Based On Explorative Data and Text Mining - A DSS for the European Home Textile Industry. Proc. of 9th Int. Conf on Ent. IS (ICEIS), Funchal, Madeira.
  2. Lakin, W.H. (2004) Euratex: European Technology Platform for the Future of textiles and clothing. A Vision for 2020. Euratex
  3. Henning, K., Backhaus, W., Rick, U. (2007) AsIsKnown - Selling through the customers eyes! Amsterdam: IOS Press, 113-120.
  4. Holten, R. (1997) Die drei Dimensionen des Inhaltsaspektes von Führungsinformationssystemen, Arbeitsberichte d. Inst. für WI, Universität Münster.
  5. Keim D. A. (2002), Information visualization and visual data mining,.IEEE Trans. Visualization and Computer Graphics, 8(1)
  6. Shneiderman, B. (1996) The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations. Proc. of the IEEE Symposium on Visual Languages, Washington. IEEE Computer Society Press
  7. Spenke,M. (2001). Visualisation and Interactive Analysis of Blood Parameters with InfoZoom. Artificial Intelligence in Medicine, volume 22, No.2, S.159-172
  8. Witten, I., Elbe, F. (2005),Data Mining. Practical Machine Learning Tools and Techniques. Morgan Kaufmann Publishers, San Francisco, second edition
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Paper Citation


in Harvard Style

Huster J., Spenke M. and Bury G. (2008). EXPLORATIVE ASSOCIATION MINING - Cross-sector Knowledge for the European Home Textile Industry . In Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-8111-37-1, pages 500-503. DOI: 10.5220/0001701105000503


in Bibtex Style

@conference{iceis08,
author={Jessica Huster and Michael Spenke and Gerrit Bury},
title={EXPLORATIVE ASSOCIATION MINING - Cross-sector Knowledge for the European Home Textile Industry},
booktitle={Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2008},
pages={500-503},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001701105000503},
isbn={978-989-8111-37-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - EXPLORATIVE ASSOCIATION MINING - Cross-sector Knowledge for the European Home Textile Industry
SN - 978-989-8111-37-1
AU - Huster J.
AU - Spenke M.
AU - Bury G.
PY - 2008
SP - 500
EP - 503
DO - 10.5220/0001701105000503