IDEAS home Printed from https://ideas.repec.org/a/wsi/ijitdm/v01y2002i04ns0219622002000373.html
   My bibliography  Save this article

Accessing Data Mining Rules Through Expert Systems

Author

Listed:
  • BASILIS BOUTSINAS

    (Department of Business Administration, University of Patras Artificial Intelligence Research Center (UPAIRC), University of Patras, 26500 Rio, Patras, Greece)

Abstract

Data mining is an emerging research area that develops techniques for knowledge discovery in huge volumes of data. Usually, data mining rules can be used either to classify data into predefined classes, or to partition a set of patterns into disjoint and homogeneous clusters, or to reveal frequent dependencies among data. The discovery of data mining rules would not be very useful unless there are mechanisms to help analysts access them in a meaningful way. Actually, documenting and reporting the extracted knowledge is of considerable importance for the successful application of data mining in practice. In this paper, we propose a methodology for accessing data mining rules, which is based on using an expert system. We present how the different types of data mining rules can be transformed into the domain knowledge of any general-purpose expert system. Then, we present how certain attribute values given by the user as facts and/or goals can determine, through a forward and/or backward chaining, the related data mining rules. In this paper, we also present a case study that demonstrates the applicability of the proposed methodology.

Suggested Citation

  • Basilis Boutsinas, 2002. "Accessing Data Mining Rules Through Expert Systems," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 1(04), pages 657-672.
    • Handle: RePEc:wsi:ijitdm:v:01:y:2002:i:04:n:s0219622002000373
    DOI: 10.1142/S0219622002000373
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219622002000373
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0219622002000373?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Carlo Alberto Magni & Stefano Malagoli & Giovanni Mastroleo, 2006. "An Alternative Approach To Firms' Evaluation: Expert Systems And Fuzzy Logic," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 5(01), pages 195-225.
    2. Boutsinas, Basilis, 2013. "Machine-part cell formation using biclustering," European Journal of Operational Research, Elsevier, vol. 230(3), pages 563-572.
    3. Magni, Carlo Alberto, 2004. "Rating and ranking firms with fuzzy expert systems: the case of Camuzzi," MPRA Paper 5889, University Library of Munich, Germany.

    More about this item

    Keywords

    Data mining; expert systems;

    Statistics

    Access and download statistics

    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:wsi:ijitdm:v:01:y:2002:i:04:n:s0219622002000373. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ijitdm/ijitdm.shtml .

    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.