Information enhancement in data mining: a study in data reduction

Barin N. Nag, Chaodong Han and Dong-qing Yao

International Journal of Data Analysis Techniques and Strategies, 2015, vol. 7, issue 1, 3-20

Abstract: Data mining can be a powerful tool for information extraction from large amounts of data. One of the techniques used to enhance the information extraction process is data reduction. Based on manufacturing industry data collected from US Economic Census, we use as an example the construction of a typology of inventory strategy according to Porter's five forces model. This study shows that data reduction (e.g., more aggregate data and fewer variables) enhances the information extracted (e.g., clearer patterns).

Keywords: data mining; data reduction; cluster analysis; supply chain strategy; inventory management; information enhancement; supply chain management; SCM; manufacturing industry. (search for similar items in EconPapers)
Date: 2015
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.inderscience.com/link.php?id=67698 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:injdan:v:7:y:2015:i:1:p:3-20

Access Statistics for this article

More articles in International Journal of Data Analysis Techniques and Strategies from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().