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Discovering Tourists’ Perception About Food by AI and NI

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Tourism Product Development in China, Asian and European Countries

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Abstract

The paper describes a very interesting study on the food tourism product. Food tourism is an important product and attraction in tourism destinations. Obtaining tourists’ perception of food can effectively promote the development of this tourism product and the destinations. The massive amount of visual information on the topic makes the study very challenging. This paper combines AI (artificial intelligence) and NI (natural intelligence) for visual content analysis to obtain the traveller’s perception of food. The Flickr YFCC 100M dataset is chosen as the data source for study. Original photos uploaded by tourists in Beijing area are screened and the home information of the travellers is retrieved. With the help of a deep learning model in computer vision, visual contents about food were filtered. The visual contents are then reclassified into several categories. Integrated with the textual analysis results, the overall food image perceived by tourists in the area was obtained.

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Acknowledgements

Thanks to National Natural Science Foundation of China (No. 51608278) for supporting this research.

Author information

Authors and Affiliations

  1. Nankai University, Tianjin, China

    Kun Zhang, Hongyu Wang & Junjiao Zhang

  2. Tianjin Modern Vocational Technology College, Tianjin, China

    Mingmin Zhu

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  1. Kun Zhang
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  2. Hongyu Wang
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  3. Junjiao Zhang
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  4. Mingmin Zhu
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Corresponding author

Correspondence to Kun Zhang .

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Editors and Affiliations

  1. University of the Balearic Islands, Palma de Mallorca, Spain

    Yuhua Luo

  2. South China University of Technology, Guangzhou, China

    Jinbo Jiang

  3. South China University of Technology, Guangzhou, China

    Doudou Bi

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Zhang, K., Wang, H., Zhang, J., Zhu, M. (2020). Discovering Tourists’ Perception About Food by AI and NI. In: Luo, Y., Jiang, J., Bi, D. (eds) Tourism Product Development in China, Asian and European Countries. Springer, Singapore. https://doi.org/10.1007/978-981-15-4447-7_2

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  • DOI: https://doi.org/10.1007/978-981-15-4447-7_2

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-4446-0

  • Online ISBN: 978-981-15-4447-7

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