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Tourist Recommender Systems Based on Emotion Recognition—A Scientometric Review

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  • Luz Santamaria-Granados

    (Facultad de Ingeniería de Sistemas, Universidad Santo Tomás Seccional Tunja, Calle 19 No. 11-64, Tunja, Boyaca 150001, Colombia)

  • Juan Francisco Mendoza-Moreno

    (Facultad de Ingeniería de Sistemas, Universidad Santo Tomás Seccional Tunja, Calle 19 No. 11-64, Tunja, Boyaca 150001, Colombia)

  • Gustavo Ramirez-Gonzalez

    (Departamento de Telemática, Universidad del Cauca, Calle 5, No. 4-70, Popayan, Cauca 190002, Colombia)

Abstract

Recommendation systems have overcome the overload of irrelevant information by considering users’ preferences and emotional states in the fields of tourism, health, e-commerce, and entertainment. This article reviews the principal recommendation approach documents found in scientific databases (Elsevier’s Scopus and Clarivate Web of Science) through a scientometric analysis in ScientoPy. Research publications related to the recommenders of emotion-based tourism cover the last two decades. The review highlights the collection, processing, and feature extraction of data from sensors and wearables to detect emotions. The study proposes the thematic categories of recommendation systems, emotion recognition, wearable technology, and machine learning. This paper also presents the evolution, trend analysis, theoretical background, and algorithmic approaches used to implement recommenders. Finally, the discussion section provides guidelines for designing emotion-sensitive tourist recommenders.

Suggested Citation

  • Luz Santamaria-Granados & Juan Francisco Mendoza-Moreno & Gustavo Ramirez-Gonzalez, 2020. "Tourist Recommender Systems Based on Emotion Recognition—A Scientometric Review," Future Internet, MDPI, vol. 13(1), pages 1-38, December.
    • Handle: RePEc:gam:jftint:v:13:y:2020:i:1:p:2-:d:467710
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    References listed on IDEAS

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    1. Fernando Reinaldo Ribeiro & Arlindo Silva & Fernando Barbosa & Ana Paula Silva & José Carlos Metrôlho, 2018. "Mobile applications for accessible tourism: overview, challenges and a proposed platform," Information Technology & Tourism, Springer, vol. 19(1), pages 29-59, June.
    2. Dimitrios Buhalis & Aditya Amaranggana, 2015. "Smart Tourism Destinations Enhancing Tourism Experience Through Personalisation of Services," Springer Books, in: Iis Tussyadiah & Alessandro Inversini (ed.), Information and Communication Technologies in Tourism 2015, edition 127, pages 377-389, Springer.
    3. Jun Zeng & Feng Li & Yinghua Li & Junhao Wen & Yingbo Wu, 2017. "Exploring the Influence of Contexts for Mobile Recommendation," International Journal of Web Services Research (IJWSR), IGI Global, vol. 14(4), pages 33-49, October.
    4. Yeh, Duen-Yian & Cheng, Ching-Hsue, 2015. "Recommendation system for popular tourist attractions in Taiwan using Delphi panel and repertory grid techniques," Tourism Management, Elsevier, vol. 46(C), pages 164-176.
    5. Animesh Chandra Roy & Mohammad Shamsul Arefin & A. S. M. Kayes & Mohammad Hammoudeh & Khandakar Ahmed, 2020. "An Empirical Recommendation Framework to Support Location-Based Services," Future Internet, MDPI, vol. 12(9), pages 1-20, September.
    6. Matthias Braunhofer & Francesco Ricci, 2017. "Selective contextual information acquisition in travel recommender systems," Information Technology & Tourism, Springer, vol. 17(1), pages 5-29, March.
    7. Li, Yunpeng & Hu, Clark & Huang, Chao & Duan, Liqiong, 2017. "The concept of smart tourism in the context of tourism information services," Tourism Management, Elsevier, vol. 58(C), pages 293-300.
    8. Federica Cena & Amon Rapp & Silvia Likavec & Alessandro Marcengo, 2018. "Envisioning the Future of Personalization Through Personal Informatics: A User Study," International Journal of Mobile Human Computer Interaction (IJMHCI), IGI Global, vol. 10(1), pages 52-66, January.
    9. Ram, Y. & Björk, P. & Weidenfeld, A., 2016. "Authenticity and place attachment of major visitor attractions," Tourism Management, Elsevier, vol. 52(C), pages 110-122.
    10. Nees Jan Eck & Ludo Waltman, 2010. "Software survey: VOSviewer, a computer program for bibliometric mapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(2), pages 523-538, August.
    11. Federica Cena & Silvia Likavec & Amon Rapp, 2019. "Real World User Model: Evolution of User Modeling Triggered by Advances in Wearable and Ubiquitous Computing," Information Systems Frontiers, Springer, vol. 21(5), pages 1085-1110, October.
    12. Matthias Braunhofer & Francesco Ricci, 0. "Selective contextual information acquisition in travel recommender systems," Information Technology & Tourism, Springer, vol. 0, pages 1-25.
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