Advanced Search
MyIDEAS: Login to save this article or follow this journal

Mining important association rules based on the RFMD technique

Contents:

Author Info

  • Yoones Asgharzadeh Sekhavat
  • Mohammad Fathian
  • Mohammad Reza Gholamian
  • Somayeh Alizadeh
Registered author(s):

    Abstract

    The method of association rule mining has been used by marketers for many years to extract marketing rules from purchase transactions. Marketers and managers employ these rules in order to predict customer needs for future sales. Extracting effective rules is one of the major problems of marketers. Effective rules can help them to make better marketing decisions. On the other hand, the Recency, Frequency, Monetary value and Duration (RFMD) method is one of the popular methods used in market segmentation that indicate profitable groups of customers. In this paper, a novel method is proposed that takes advantage of the RFMD method to extract effective association rules from profitable segments of purchase transactions. In other words, in the first step, raw data are classified based on the RFMD technique; and in the second step, effective association rules are extracted from sections with high RFMD values. The proposed method employs a new Maximum Frequent Itemset Extractor (MFIE) algorithm that outperforms the classic algorithm (Apriori) in extracting frequent itemsets from a large number of transactions. In addition, unlike most of the previous central methods, the proposed method is designed for extracting association rules from distributed databases.

    Download Info

    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: http://www.inderscience.com/link.php?id=30008
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

    Bibliographic Info

    Article provided by Inderscience Enterprises Ltd in its journal Int. J. of Data Analysis Techniques and Strategies.

    Volume (Year): 2 (2010)
    Issue (Month): 1 ()
    Pages: 1-21

    as in new window
    Handle: RePEc:ids:injdan:v:2:y:2010:i:1:p:1-21

    Contact details of provider:
    Web page: http://www.inderscience.com/browse/index.php?journalID=282

    Related research

    Keywords: association rules; recency frequency monetary value duration; RFMD; maximum frequent itemset; data analysis; data mining; marketing rules; purchase transactions; market segmentation.;

    References

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

    Citations

    Lists

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

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:ids:injdan:v:2:y:2010:i:1:p:1-21. 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: (Graham Langley).

    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.