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Machine Learning in Health and Wellness Tourism

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HCI International 2023 – Late Breaking Papers (HCII 2023)

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Abstract

Health and Wellness Tourism consumers are customers of specific kinds of products, such as luxury hotels, while other perspectives center on recovery, well-being, removing stress, and promoting peer socialization. While others prefer other service categories like personnel health service, health promotion treatments, environment, healthy diet, relaxation, social activities, and the experience of unique tourism resources. The objective of this paper is to identify potential customers through the segmentation of the guests and identify some rules to achieve a specific type of customer. We used Unsupervised Algorithms through the k-Means clustering algorithm by Orange Data Mining and Power BI software. The results of the K-means algorithm identify four clusters: C1 – constituted only by the majority of couples without babies and children, C2 – constituted by Couples with babies and very few children, C3 -Couples with few children, and C4 Couples with several children. Also, we used the Frequent Pattern Mining Algorithm and we found that it is possible to identify some rules that help to learn about consumer behavior.

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Acknowledgments

This paper is financed by National Funds provided by FCT- Foundation for Science and Technology through project UIDB/04020/2020 and project Guest-IC I&DT nr. 047399 financed by CRESC ALGARVE2020, PORTUGAL2020 and FEDER.

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Authors and Affiliations

  1. ESGHT, CinTurs, University of Algarve, 8005-139, Faro, Portugal

    Célia M. Q. Ramos & Rashed Isam Ashqar

  2. CEFAGE, Faro, Portugal

    Célia M. Q. Ramos

Authors
  1. Célia M. Q. Ramos
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  2. Rashed Isam Ashqar
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Corresponding author

Correspondence to Célia M. Q. Ramos .

Editor information

Editors and Affiliations

  1. Cyprus University of Technology, Limassol, Cyprus

    Panayiotis Zaphiris

  2. Cyprus University of Technology, Limassol, Cyprus

    Andri Ioannou

  3. Soar Technology, Inc., Orlando, FL, USA

    Robert A. Sottilare

  4. Fraunhofer FKIE, Wachtberg, Germany

    Jessica Schwarz

  5. City University of Hong Kong, Hong Kong, Hong Kong

    Fiona Fui-Hoon Nah

  6. City University of Hong Kong, Hong Kong, Hong Kong

    Keng Siau

  7. University of West Florida, Pensacola, FL, USA

    June Wei

  8. University of Central Florida, Orlando, FL, USA

    Gavriel Salvendy

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Ramos, C.M.Q., Ashqar, R.I. (2023). Machine Learning in Health and Wellness Tourism. In: Zaphiris, P., et al. HCI International 2023 – Late Breaking Papers. HCII 2023. Lecture Notes in Computer Science, vol 14060. Springer, Cham. https://doi.org/10.1007/978-3-031-48060-7_39

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  • DOI: https://doi.org/10.1007/978-3-031-48060-7_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-48059-1

  • Online ISBN: 978-3-031-48060-7

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