IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v12y2020i12p212-d451932.html
   My bibliography  Save this article

About Rule-Based Systems: Single Database Queries for Decision Making

Author

Listed:
  • Piotr Artiemjew

    (Faculty of Mathematics and Computer Science, University of Warmia and Mazury in Olsztyn, 10-710 Olsztyn, Poland)

  • Lada Rudikova

    (Faculty of Mathematics and Computer Science, Grodno State Yanka Kupala University, Street. Ozheshko 22, 230023 Grodno, Belarus)

  • Oleg Myslivets

    (Faculty of Mathematics and Computer Science, Grodno State Yanka Kupala University, Street. Ozheshko 22, 230023 Grodno, Belarus)

Abstract

One of the developmental directions of Future Internet technologies is the implementation of artificial intelligence systems for manipulating data and the surrounding world in a more complex way. Rule-based systems, very accessible for people’s decision-making, play an important role in the family of computational intelligence methods. The use of decision-making rules along with decision trees are one of the simplest forms of presenting complex decision-making processes. Decision support systems, according to the cross-industry standard process for data mining (CRISP-DM) framework, require final embedding of the learned model in a given computer infrastructure, integrated circuits, etc. In this work, we deal with the topic concerning placing the learned rule-based model of decision support in the database environment-exactly in the SQL database tables. Our main goal is to place the previously trained model in the database and apply it by means of single queries. In our work we assume that the decision-making rules applied are mutually consistent and additionally the Minimal Description Length (MDL) rule is introduced. We propose a universal solution for any IF THEN rule induction algorithm.

Suggested Citation

  • Piotr Artiemjew & Lada Rudikova & Oleg Myslivets, 2020. "About Rule-Based Systems: Single Database Queries for Decision Making," Future Internet, MDPI, vol. 12(12), pages 1-13, November.
  • Handle: RePEc:gam:jftint:v:12:y:2020:i:12:p:212-:d:451932
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/12/12/212/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1999-5903/12/12/212/
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Filipe Portela, 2021. "Data Science and Knowledge Discovery," Future Internet, MDPI, vol. 13(7), pages 1-4, July.

    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:gam:jftint:v:12:y:2020:i:12:p:212-:d:451932. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.