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TechTalk with AI Recommendation System in Smart Tourism by Prof. Francesco Ricci

  • Suejung Kang (Smart Tourism Education Platform, College of Hotel and Tourism Management, Kyung Hee University) ;
  • Chulmo Koo (Smart Tourism Education Platform, College of Hotel and Tourism Management, Kyung Hee University)
  • Received : 2022.01.12
  • Accepted : 2022.03.10
  • Published : 2023.06.30

Abstract

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References

  1. Baltrunas, L., Makcinskas, T., & Ricci, F. (2010). Group recommendations with rank aggregation and collaborative filtering. Proceedings of the Fourth ACM Conference on Recommender Systems, Association for Computing Machinery, New York, NY, USA, 119-126.
  2. Massimo, D., & Ricci, F. (2021). Next-POI Recommendations Matching User's Visit Behaviour. In W. Wo rndl, C. Koo, & J. L. Stienmetz (Eds.), Information and Communication Technologies in Tourism 2021 (pp 45-57). Springer, Cham.
  3. Pilliponyte, G., Massimo, D., & Ricci, F. (2023). The impact of personalised advertisement campaigns on tourist choices in South Tyrol: A sustainable tourism perspective. UMAP '23 Adjunct: Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization, 100-103.
  4. Ricci, F., Rokach, L., & Shapira, B. (2022). Recommender systems handbook. New York: Springer-Verlag New York, Inc.
  5. Werthner, H., & Ricci, F. (2004). E-commerce and tourism. Communications of the ACM, 47(12), 101-105. https://doi.org/10.1145/1035134.1035141