IDEAS home Printed from https://ideas.repec.org/a/ids/ijdmmm/v11y2019i4p350-365.html
   My bibliography  Save this article

Fast parallel PageRank technique for detecting spam web pages

Author

Listed:
  • Nilay Khare
  • Hema Dubey

Abstract

Brin and Larry proposed PageRank in 1998, which appears as a prevailing link analysis technique used by web search engines to rank its search results list. Computation of PageRank values in an efficient and faster manner for very immense web graph is truly an essential concern for search engines today. To identify the spam web pages and also deal with them is yet another important concern in web browsing. In this research article, an efficient and faster parallel PageRank algorithm is proposed, which harnesses the power of graphics processing units (GPUs). In proposed algorithm, the PageRank scores are non-uniformly distributes among the web pages, so it is also competent of coping with spam web pages. The experiments are performed on standard datasets available in Stanford large network dataset collection. There is a speed up of about 1.1 to 1.7 for proposed parallel PageRank algorithm over existing parallel PageRank algorithm.

Suggested Citation

  • Nilay Khare & Hema Dubey, 2019. "Fast parallel PageRank technique for detecting spam web pages," International Journal of Data Mining, Modelling and Management, Inderscience Enterprises Ltd, vol. 11(4), pages 350-365.
    • Handle: RePEc:ids:ijdmmm:v:11:y:2019:i:4:p:350-365
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=102720
    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:ijdmmm:v:11:y:2019:i:4:p:350-365. 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=342 .

    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.