IDEAS home Printed from https://ideas.repec.org/a/bjc/journl/v7y2020i6p113-116.html
   My bibliography  Save this article

Visitor Navigation Pattern Prediction Using Transition Matrix Compression

Author

Listed:
  • Ei Theint Theint Thu

    (Faculty of Information Science,University of Computer Studies, Hinthada, Myanmar)

  • Aye Aye Nyein

    (Faculty of Information Science,University of Computer Studies, Hinthada, Myanmar)

  • Hlaing Htake Khaung Tin

    (Faculty of Information Science,University of Computer Studies, Hinthada, Myanmar)

Abstract

As an increasing number of cities consists of an increasing number of visiting places, it is more difficult for the visitors to consider. Meanwhile, the system tries to introduce recommendation features to their visitors. The main aim of this paper is to only implement visitor navigation pattern prediction system in Myanmar. The paper uses traveling paths that assist visitors to navigate the visiting places based on the past visitor’s behavior. To cluster the paths with similar transition behavior and compress the transition matrix to an best size for efficient probability calculation in paths, transition probability matrix compression has been used. In this paper, Visitor Navigation Pattern Prediction Using Transition Matrix Compression is developed. It uses data mining techniques for recommending a visitor which (next)paths is closely the most popular paths in Myanmar. By looking at the traveling paths in the organization, the system can know the popular paths(places).

Suggested Citation

  • Ei Theint Theint Thu & Aye Aye Nyein & Hlaing Htake Khaung Tin, 2020. "Visitor Navigation Pattern Prediction Using Transition Matrix Compression," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 7(6), pages 113-116, June.
    • Handle: RePEc:bjc:journl:v:7:y:2020:i:6:p:113-116
    as

    Download full text from publisher

    File URL: https://www.rsisinternational.org/journals/ijrsi/digital-library/volume-7-issue-6/113-116.pdf
    Download Restriction: no
    File URL: https://www.rsisinternational.org/virtual-library/papers/visitor-navigation-pattern-prediction-using-transition-matrix-compression/
    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:bjc:journl:v:7:y:2020:i:6:p:113-116. 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: Dr. Renu Malsaria (email available below). General contact details of provider: https://www.rsisinternational.org/journals/ijrsi/ .

    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.