Trends In Tourism Recommendation Systems: A Review

Trends In Tourism Recommendation Systems: A Review

Authors

  • Aderline Song Ke Xin Design and Technology Centre, University of Technology Sarawak, No 1, Jalan Universiti, Sibu, Sarawak, Malaysia
  • Huong Yong Ting Design and Technology Centre, University of Technology Sarawak, No 1, Jalan Universiti, Sibu, Sarawak, Malaysia
  • Abdulwahab Funsho Atanda Design and Technology Centre, University of Technology Sarawak, No 1, Jalan Universiti, Sibu, Sarawak, Malaysia

Keywords:

Tourism Recommendation System, Recommendation System, Sustainable tourism, Smart Tourism, Travel Recommendation System

Abstract

Tourism Recommendation Systems (TRS) are increasingly important in the tourism industry to provide personalized recommendations based on diverse tourist preferences. Technology and big data have transformed TRS from traditional travel agencies to modern digital platforms, enabling the processing of vast amounts of user-generated data for precise recommendations. The study aims to identify strengths and weaknesses within existing TRS frameworks and techniques, propose recommendations to mitigate these weaknesses, and provide insights for practitioners and researchers. Key findings are the effectiveness of personalized and context-aware recommendations, the importance of multimodal data integration, the need for ethical and fair recommendation practices. Future directions in TRS research should focus on exploring and developing explainable AI and transparency, personalization at scale, enhancing multimodal recommendation capabilities, and ensuring ethical and fair recommendation.  This review contributes to a deeper understanding of contemporary TRS methodologies and provides actionable insights for enhancing TRS performance. By addressing current trends and proposing recommendations for future research, this paper aims to advance the field of TRS and improve travel experiences for tourists.

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Author Biographies

Aderline Song Ke Xin, Design and Technology Centre, University of Technology Sarawak, No 1, Jalan Universiti, Sibu, Sarawak, Malaysia

Aderline Song Ke Xin is a Master’s student in Computing at the University of Technology Sarawak, engaged in a research-focused program. She earned her Bachelor of Computer Science (Hons) with First Class Honours, a degree recognized by Malaysian Ministry of Higher Education (MoHE) and accredited by Malaysian Qualifications Agency (MQA). Her current research is focused on AI-based travel itinerary generation using AI models to optimize travel plans. Aderline is available for contact via email at mic23090001@student.uts.edu.my.

Huong Yong Ting , Design and Technology Centre, University of Technology Sarawak, No 1, Jalan Universiti, Sibu, Sarawak, Malaysia

Alan Ting Huong Yong, PhD, serves as the Dean, School of Computing and Creative Media with affiliations to the Malaysia Board of Technologists (MBOT), the Board of Engineers Malaysia (BEM), and Institution of Engineers (IEM) at University of Technology Sarawak. He earned his PhD from Multimedia University (MMU) and specializes in Computer Vision, Soft Computing, and 3D Imaging. His research primarily focuses on computer vision, soft computing, and 3D imaging. His research contributions are recognized in these fields. He can be contacted via email at alan.ting@uts.edu.my.

 

Abdulwahab Funsho Atanda, Design and Technology Centre, University of Technology Sarawak, No 1, Jalan Universiti, Sibu, Sarawak, Malaysia

Abdulwahab Funsho Atanda holds a PhD in Computer Science from Universiti Utara Malaysia and has also earned Master's degrees in Computer Science from the University of Ibadan and Business Administration from the University of Ilorin, both in Nigeria. He is currently associated with the School of Computing & Creative Media, specializing in Artificial Intelligence, Machine Learning, and Drone Technology. His academic and research pursuits integrate advanced computing technologies with practical business applications. Abdulwahab can be contacted via email at funsho.atanda@uts.edu.my.

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2024-09-01

How to Cite

Song Ke Xin, A., Ting , H. Y., & Atanda, A. F. (2024). Trends In Tourism Recommendation Systems: A Review. Journal of Computing Research and Innovation, 9(2), 85–107. Retrieved from https://jcrinn.com/index.php/jcrinn/article/view/438

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General Computing
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