IDEAS home Printed from https://ideas.repec.org/a/ids/ijitma/v23y2024i3-4p206-218.html
   My bibliography  Save this article

Research on fast mining of enterprise marketing investment databased on improved association rules

Author

Listed:
  • Yinghui Liu
  • Xiaosi Xu
  • Qixing Yin

Abstract

Because of the problems of low mining precision and slow mining speed in traditional enterprise marketing investment data mining methods, a fast mining method for enterprise marketing investment databased on improved association rules is proposed. First, the enterprise marketing investment data is collected through the crawler framework, and then the collected data is cleaned. Then, the cleaned data features are extracted, and the correlation degree between features is calculated. Finally, according to the calculation results, all data items are used as constraints to reduce the number of frequent itemsets. A pruning strategy is designed in advance. Combined with the constraints, the Apriori algorithm of association rules is improved, and the improved algorithm is used to calculate all frequent itemsets, Obtain fast mining results of enterprise marketing investment data. The experimental results show that the proposed method is fast and accurate in data mining of enterprise marketing investment.

Suggested Citation

  • Yinghui Liu & Xiaosi Xu & Qixing Yin, 2024. "Research on fast mining of enterprise marketing investment databased on improved association rules," International Journal of Information Technology and Management, Inderscience Enterprises Ltd, vol. 23(3/4), pages 206-218.
  • Handle: RePEc:ids:ijitma:v:23:y:2024:i:3/4:p:206-218
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=139592
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ids:ijitma:v:23:y:2024:i:3/4:p:206-218. See general information about how to correct material in RePEc.

    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.

    We have no bibliographic references for this item. You can help adding them by using 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 RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=18 .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.