IDEAS home Printed from https://ideas.repec.org/a/ibn/masjnl/v3y2009i10p27.html
   My bibliography  Save this article

Applications of Support Vector Machine Based on Boolean Kernel to Spam Filtering

Author

Listed:
  • Shugang Liu
  • Kebin Cui

Abstract

Spam is so widely speared that has a bad effect on daily use of E-mail. Nowadays, among the primary technologies of spam filtering, support vector machine (SVM) is applied widely, because it is efficient and has high separating accuracy. The main problem of support vector machine arithmetic is how to choose the kernel function. To solve this problem people propose spam filtering arithmetic of support vector machine based on Boolean kernel. The arithmetic uses filtering methods based on attributes, such as IP address, subject words, keywords in content, enclosure information, etc. These attributes compose the feature vectors, and the vectors are classified by SVM-MDNF based on Boolean kernel. The experiment results show that this arithmetic has high separating accuracy, high recall ratio and precision ratio. The arithmetic has its value in theory and application.

Suggested Citation

  • Shugang Liu & Kebin Cui, 2009. "Applications of Support Vector Machine Based on Boolean Kernel to Spam Filtering," Modern Applied Science, Canadian Center of Science and Education, vol. 3(10), pages 1-27, October.
    • Handle: RePEc:ibn:masjnl:v:3:y:2009:i:10:p:27
    as

    Download full text from publisher

    File URL: https://ccsenet.org/journal/index.php/mas/article/download/3936/3463
    Download Restriction: no
    File URL: https://ccsenet.org/journal/index.php/mas/article/view/3936
    Download Restriction: no
    ---><---

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    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:ibn:masjnl:v:3:y:2009:i:10:p:27. 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: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.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.