IDEAS home Printed from https://ideas.repec.org/a/ids/ijenma/v14y2023i3p268-282.html
   My bibliography  Save this article

Opinion mining of customers reviews using new Jaccard dissimilarity kernel function

Author

Listed:
  • Santhosh Kumar Arjunan
  • Punniyamoorthy Murugesan
  • Ernest Johnson

Abstract

Opinion mining (aka sentiment mining), a subdivision of text classification has become traction among researchers in recent decades, due to the popularity of its practical application in real-time scenarios like product reviews, politics, movies, etc. Various machine learning algorithms are used to identify the document or sentence opinions which are available in social space. SVM is one of the most popular supervised machine learning algorithms and uses kernel function to classify data when the data points are nonlinearly separable. In this paper, we have proposed a new Kernel function called Jaccard dissimilarity Kernel functions where the distance between the two binary vectors is classified based on principle of Jaccard coefficient. In our study, we used this Jaccard Kernel function to classify the opinions of the recent Bollywood movie reviews in to positive and negative.

Suggested Citation

  • Santhosh Kumar Arjunan & Punniyamoorthy Murugesan & Ernest Johnson, 2023. "Opinion mining of customers reviews using new Jaccard dissimilarity kernel function," International Journal of Enterprise Network Management, Inderscience Enterprises Ltd, vol. 14(3), pages 268-282.
    • Handle: RePEc:ids:ijenma:v:14:y:2023:i:3:p:268-282
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=132966
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    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:ids:ijenma:v:14:y:2023:i:3:p:268-282. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=187 .

    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.