IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v40y1994i6p685-707.html
   My bibliography  Save this article

Rule Management in Expert Database Systems

Author

Listed:
  • Arie Segev

    (Walter A. Haas School of Business, The University of California and Information and Computing Sciences Division, Lawrence Berkeley Laboratory, Berkeley, California 94720)

  • J. Leon Zhao

    (Graduate School of Business Administration, The College of William and Mary, Williamsburg, Virginia 23187)

Abstract

Expert database systems combine database and expert systems technologies to support the effective management of both rules and data. This paper studies rule processing strategies in expert database systems involving rules that are conditional on joins of relational data. Auxiliary constructs for processing join rules are proposed, and a framework of join rule processing strategies is developed. Cost functions of several strategies are derived based on a stochastic model that characterizes the arrival processes of transactions and queries to the database. Performance evaluation shows that the proposed data constructs and strategies provide an effective method for processing rules.

Suggested Citation

  • Arie Segev & J. Leon Zhao, 1994. "Rule Management in Expert Database Systems," Management Science, INFORMS, vol. 40(6), pages 685-707, June.
    • Handle: RePEc:inm:ormnsc:v:40:y:1994:i:6:p:685-707
    DOI: 10.1287/mnsc.40.6.685
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.40.6.685
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.40.6.685?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
    ---><---

    Citations

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


    Cited by:

    1. Akhil Kumar & J. Leon Zhao, 1999. "Dynamic Routing and Operational Controls in Workflow Management Systems," Management Science, INFORMS, vol. 45(2), pages 253-272, February.
    2. Anindya Datta & Igor R. Viguier, 2000. "Handling Sensor Data in Rapidly Changing Environments to Support Soft Real-Time Requirements," INFORMS Journal on Computing, INFORMS, vol. 12(2), pages 84-103, May.
    3. Sumit Sarkar & Mysore Ramaswamy, 2000. "Knowledge Base Decomposition to Facilitate Verification," Information Systems Research, INFORMS, vol. 11(3), pages 260-283, September.

    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:inm:ormnsc:v:40:y:1994:i:6:p:685-707. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.