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Assessing language discrepancies between travelers and online travel recommendation systems: Application of the Jaccard distance score to web data mining

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  • Park, Sangwon
  • Kim, Dae-Young

Abstract

By using a human-centric approach to online recommender systems, this research aims to estimate the language discrepancies of which travelers and destination marketers describe the travel experiences across 11 tourism destinations in USA. In order to address the research purpose, data has been collected from two different sources that reflect the views of travelers and service providers. Then, a set of text data mining methods (i.e., clustering analysis and Jaccard distance score) was applied to identify the language differences between travelers and CVB websites, according to the following categories: shopping, dining, nightlife/activities, and attractions. Some possible methodological extensions that can improve recommendation capabilities, and managerial implications of these findings are provided.

Suggested Citation

  • Park, Sangwon & Kim, Dae-Young, 2017. "Assessing language discrepancies between travelers and online travel recommendation systems: Application of the Jaccard distance score to web data mining," Technological Forecasting and Social Change, Elsevier, vol. 123(C), pages 381-388.
    • Handle: RePEc:eee:tefoso:v:123:y:2017:i:c:p:381-388
    DOI: 10.1016/j.techfore.2017.03.031
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. Stepchenkova, Svetlana & Tang, Liang & Jang, SooCheong (Shawn) & Kirilenko, Andrei P. & Morrison, Alastair M., 2010. "Benchmarking CVB website performance: Spatial and structural patterns," Tourism Management, Elsevier, vol. 31(5), pages 611-620.
    4. K. Coussement & D. van den Poel, 2008. "Integrating the voice of customers through call center emails into a decision support system for churn prediction," Post-Print hal-00788086, HAL.
    5. Park, Sangwon & Nicolau, Juan L., 2015. "Asymmetric effects of online consumer reviews," Annals of Tourism Research, Elsevier, vol. 50(C), pages 67-83.
    6. Gerald Häubl & Valerie Trifts, 2000. "Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids," Marketing Science, INFORMS, vol. 19(1), pages 4-21, May.
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    Cited by:

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    3. Jaroslav Mašek & Vladimíra Štefancová & Jaroslav Mazanec & Petra Juránková, 2023. "The Classification of Application Users Supporting and Facilitating Travel Mobility Using Two-Step Cluster Analysis," Mathematics, MDPI, vol. 11(9), pages 1-16, May.

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