IDEAS home Printed from https://ideas.repec.org/a/wsi/ijitdm/v20y2021i01ns0219622020500522.html
   My bibliography  Save this article

A Hotel Recommender System for Tourists Using the Artificial Bee Colony Algorithm and Fuzzy TOPSIS Model: A Case Study of TripAdvisor

Author

Listed:
  • Saman Forouzandeh

    (Department of Computer Engineering, University of Applied Science and Technology, Center of Tehran Municipality ICT org., Tehran, Iran)

  • Kamal Berahmand

    (#x2020;Department of Science and Engineering, Queensland University of Technology, Brisbane, Australia)

  • Elahe Nasiri

    (#x2021;Department of Information Technology and Communications, Azarbaijan Shahid Madani University, Tabriz, Iran)

  • Mehrdad Rostami

    (#xA7;Department of Computer Engineering, University of Kurdistan, Sanandaj, Iran)

Abstract

Recommendation systems play an indispensable role in tourists’ decision-making process. An important issue for tourists concerns the selection of accommodation in accordance with the criteria on their minds, which may include several items at the same time. This paper proposes a novel approach to recommendation systems in the tourism industry involving a combination of the Artificial Bee Colony (ABC) algorithm and the fuzzy TOPSIS model. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), a multi-criteria decision-making method, has been utilized to optimize the system. The solution presented in this research includes two major parts, where the employed ABC algorithm has been improved and is more efficient than the standard version. This research has addressed the TripAdvisor dataset and presented a method for hotel recommendations based on user preferences according to real data. The obtained results demonstrate the high accuracy of the method presented in the research.

Suggested Citation

  • Saman Forouzandeh & Kamal Berahmand & Elahe Nasiri & Mehrdad Rostami, 2021. "A Hotel Recommender System for Tourists Using the Artificial Bee Colony Algorithm and Fuzzy TOPSIS Model: A Case Study of TripAdvisor," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 20(01), pages 399-429, January.
    • Handle: RePEc:wsi:ijitdm:v:20:y:2021:i:01:n:s0219622020500522
    DOI: 10.1142/S0219622020500522
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219622020500522
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0219622020500522?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rakhi Saxena & Sharanjit Kaur & Harita Ahuja & Sunita Narang, 2024. "Leveraging item attribute popularity for group recommendation," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(6), pages 2645-2655, June.

    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:wsi:ijitdm:v:20:y:2021:i:01:n:s0219622020500522. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ijitdm/ijitdm.shtml .

    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.