Skip to main content
Have a personal or library account? Click to login
Tourism destination Recommender Systems: A Scoping Review and Thematic Clustering of Scientific Literature Cover

Tourism destination Recommender Systems: A Scoping Review and Thematic Clustering of Scientific Literature

Open Access
|Jul 2026

References

  1. Abbasi-Moud, Z., Hosseinabadi, S., Kelarestaghi, M., & Eshghi, F. (2022). CAFOB: Context-aware fuzzy-ontology-based tourism recommendation system. Expert Systems with Applications, 199, 116877.
  2. Abbasi-Moud, Z., Vahdat-Nejad, H., & Sadri, J. (2021). Tourism recommendation system based on semantic clustering and sentiment analysis. Expert Systems with Applications, 167, 114324. https://doi.org/10.1016/j.eswa.2020.114324
  3. Batet, M., Moreno, A., Sánchez, D., Isern, D., & Valls, A. (2012). Turist@: Agent-based personalised recommendation of tourist activities. Expert systems with applications, 39(8), 7319-7329. https://doi.org/10.1016/j.eswa.2012.01.086
  4. Cepeda-Pacheco, J. C., & Domingo, M. C. (2022). Deep learning and Internet of Things for tourist attraction recommendations in smart cities. Neural Computing and Applications, 34(10), 7691-7709.
  5. Choi, I. Y., Ryu, Y. U., & Kim, J. K. (2021). A recommender system based on personal constraints for smart tourism city. Asia Pacific Journal of Tourism Research, 26(4), 440-453.
  6. Cuc, L. D., Pantea, M. F., Rad, D., Trifan, V. A., & Țurlea, I. C. (2024). Does culinary nostalgia shape touristic behaviour?. The AMFITEATRU ECONOMIC journal, 26(Special 18), 1126-1126.
  7. Cuc, L. D., Rad, D., Hațegan, C. D., Trifan, V. A., & Ardeleanu, T. (2024). The Mediating Role of the Financial Recommender System Advising Acceptance in the Relationship between Investments Trust and Decision-Making Behavior. In Proceedings of the International Conference on Business Excellence (Vol. 18, No. 1, pp. 2260-2273). Sciendo.
  8. Delic, A., Neidhardt, J., Nguyen, T. N., & Ricci, F. (2018). An observational user study for group recommender systems in the tourism domain. Information Technology & Tourism, 19(1), 87-116.
  9. Figueredo, M., Ribeiro, J., Cacho, N., Thome, A., Cacho, A., Lopes, F., & Araujo, V. (2018, March). From photos to travel itinerary: A tourism recommender system for smart tourism destination. In 2018 IEEE Fourth International Conference on Big Data Computing Service and Applications (BigDataService) (pp. 85-92). IEEE.
  10. Garcia, I., Sebastia, L., & Onaindia, E. (2011). On the design of individual and group recommender systems for tourism. Expert systems with applications, 38(6), 7683-7692. https://doi.org/10.1016/j.eswa.2010.12.143
  11. Garcia, I., Sebastia, L., & Onaindia, E. (2011). On the design of individual and group recommender systems for tourism. Expert systems with applications, 38(6), 7683-7692.
  12. Gavalas, D., & Kenteris, M. (2011). A web-based pervasive recommendation system for mobile tourist guides. Personal and Ubiquitous Computing, 15(7), 759-770. https://doi.org/10.1007/s00779-011-0389-x
  13. Kbaier, M. E. B. H., Masri, H., & Krichen, S. (2017). A personalized hybrid tourism recommender system. In 2017 IEEE/ACS 14th international conference on computer systems and applications (AICCSA)(pp. 244–250).
  14. Kesorn, K., Juraphanthong, W., & Salaiwarakul, A. (2017). Personalized attraction recommendation system for tourists through check-in data. IEEE access, 5, 26703-26721.
  15. Kolahkaj, M., Harounabadi, A., Nikravanshalmani, A., & Chinipardaz, R. (2020). A hybrid context-aware approach for e-tourism package recommendation based on asymmetric similarity measurement and sequential pattern mining. Electronic Commerce Research and Applications, 42, 100978.
  16. Lile, R., Cuc, L. D., Pantea, M. F., & Rad, D. (2024). A Humanistic Approach to Recommender Systems: Implications for 5.0 Marketing Management. In Romanian Management Theory and Practice: Navigating Digitization and Internationalization in the New Global Economy (pp. 163-178). Cham: Springer Nature Switzerland.
  17. Lucas, J. P., Luz, N., Moreno, M. N., Anacleto, R., Figueiredo, A. A., & Martins, C. (2013). A hybrid recommendation approach for a tourism system. Expert systems with applications, 40(9), 3532-3550.
  18. Majid, A., Chen, L., Chen, G., Mirza, H. T., Hussain, I., & Woodward, J. (2013). A context-aware personalized travel recommendation system based on geotagged social media data mining. International Journal of Geographical Information Science, 27(4), 662-684.
  19. Moreno, A., Valls, A., Isern, D., Marin, L., & Borràs, J. (2013). Sigtur/e-destination: ontology-based personalized recommendation of tourism and leisure activities. Engineering applications of artificial intelligence, 26(1), 633-651. https://doi.org/10.1016/j.engappai.2012.02.014
  20. Nilashi, M., Bagherifard, K., Rahmani, M., & Rafe, V. (2017). A recommender system for tourism industry using cluster ensemble and prediction machine learning techniques. Computers & industrial engineering, 109, 357-368. https://doi.org/10.1016/j.cie.2017.05.016
  21. Pantano, E., Priporas, C. V., Stylos, N., & Dennis, C. (2019). Facilitating tourists’ decision making through open data analyses: A novel recommender system. Tourism Management Perspectives, 31, 323-331.
  22. Rad, D., Cuc, L. D., Feher, A., Joldeș, C. S. R., Bâtcă-Dumitru, G. C., Șendroiu, C., ... & Popescu, M. G. (2023). The influence of social stratification on trust in recommender systems. Electronics, 12(10), 2160.
  23. Rad, D., Cuc, L. D., Lile, R., Cuc, P. N., Pantea, M. F., & Anta, D. (2023). Suspiciousness and fast and slow thinking impact on trust in recommender systems. In Proceedings of the International Conference on Business Excellence (Vol. 17, No. 1, pp. 1103-1118). Sciendo.
  24. Shen, J., Deng, C., & Gao, X. (2016). Attraction recommendation: Towards personalized tourism via collective intelligence. Neurocomputing, 173, 789-798.
  25. Solano-Barliza, A., Arregocés-Julio, I., Aarón-Gonzalvez, M., Zamora-Musa, R., De-La-Hoz-Franco, E., Escorcia-Gutierrez, J., & Acosta-Coll, M. (2024). Recommender systems applied to the tourism industry: a literature review. Cogent Business & Management, 11(1), 2367088.
  26. Van Setten, M., Pokraev, S., & Koolwaaij, J. (2004, August). Context-aware recommendations in the mobile tourist application COMPASS. In International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems (pp. 235-244). Berlin, Heidelberg: Springer Berlin Heidelberg.
  27. Yang, X., Zhang, L., & Feng, Z. (2024). Personalized tourism recommendations and the E-tourism user experience. Journal of Travel Research, 63(5), 1183-1200.
  28. Yoon, J., & Choi, C. (2023). Real-time context-aware recommendation system for tourism. Sensors, 23(7), 3679.
Language: English
Page range: 3836 - 3849
Published on: Jul 22, 2026
Published by: Bucharest University of Economic Studies
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2026 Raul LILE, Andreea ZAMFIR, Ramona LILE, Rad GAVRIL, published by Bucharest University of Economic Studies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.