IDEAS home Printed from https://ideas.repec.org/a/igg/jbir00/v3y2012i1p72-82.html
   My bibliography  Save this article

Optimizing the Accuracy of Entity-Based Data Integration of Multiple Data Sources Using Genetic Programming Methods

Author

Listed:
  • Yinle Zhou

    (University of Arkansas at Little Rock, USA)

  • Ali Kooshesh

    (Sonoma State University, USA)

  • John Talburt

    (University of Arkansas at Little Rock, USA)

Abstract

Entity-based data integration (EBDI) is a form of data integration in which information related to the same real-world entity is collected and merged from different sources. It often happens that not all of the sources will agree on one value for a common attribute. These cases are typically resolved by invoking a rule that will select one of the non-null values presented by the sources. One of the most commonly used selection rules is called the naïve selection operator that chooses the non-null value provided by the source with the highest overall accuracy for the attribute in question. However, the naïve selection operator will not always produce the most accurate result. This paper describes a method for automatically generating a selection operator using methods from genetic programming. It also presents the results from a series of experiments using synthetic data that indicate that this method will yield a more accurate selection operator than either the naïve or naïve-voting selection operators.

Suggested Citation

  • Yinle Zhou & Ali Kooshesh & John Talburt, 2012. "Optimizing the Accuracy of Entity-Based Data Integration of Multiple Data Sources Using Genetic Programming Methods," International Journal of Business Intelligence Research (IJBIR), IGI Global, vol. 3(1), pages 72-82, January.
    • Handle: RePEc:igg:jbir00:v:3:y:2012:i:1:p:72-82
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jbir.2012010105
    Download Restriction: no
    ---><---

    More about this item

    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:igg:jbir00:v:3:y:2012:i:1:p:72-82. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.