IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to save this article

Using Data Mining Techniques in Economic Crisis

Listed author(s):
  • Codreanu Diana Elena


    („Constantin Brancoveanu” University of Pitesti)

  • Popa Ionela


    („Constantin Brancoveanu” University of Pitesti)

  • Parpandel Denisa Elena


    („Constantin Brancoveanu” University of Pitesti)

Current economic context marked by economic crisis, has the effect of reducing costs and greater control over costs. It is a problem faced by all managers and a solution to anti-crisis measures such as using data mining techniques. Data mining or "knowledge discovery in large databases" is a set of techniques used to discover valuable information from large volumes of data unknown .Data mining techniques are used in many fields, one which lends itself particularly well to the economy. Uncertainty facing the economy makes use of data mining techniques are more important now as it assumes that there are many advantages, brings both knowledge and management level in their area of activity.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL:
Download Restriction: no

Article provided by Ovidius University of Constantza, Faculty of Economic Sciences in its journal Ovidius University Annals, Economic Sciences Series.

Volume (Year): XI (2011)
Issue (Month): 2 (May)
Pages: 233-236

in new window

Handle: RePEc:ovi:oviste:v:xi:y:2011:i:9:p:233-236
Contact details of provider: Web page:

More information through EDIRC

No references listed on IDEAS
You can help add them by filling out this form.

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:ovi:oviste:v:xi:y:2011:i:9:p:233-236. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Gheorghiu Gabriela)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.