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Xi’an tourism destination image analysis via deep learning

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Abstract

Existing methods focus on destination image construction by textual description or visual content separately. However, descriptions and images are closely related since they are taken from the same reviews and represent tourists impression of the city. It’s questionable to study them separately. In this paper, we used both images and descriptions from the reviews to construct Xi’an tourism destination image. More concretely, scene recognition, landmark recognition and food image recognition are utilized to obtain visual image. Lexical analysis is applied to obtain semantic image. We further compared the differences between visual image and semantic image then we proposed the fusion image. Finally, the top 300 key words and differences of the photo contents between the adjacent 2 years are selected to discovering new changes of the destination image. Results show that the visual image and semantic image are significant different from each other and the new changes of semantic image are closely related to the events or things that happened in that year and changes of visual image are not significant.

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Acknowledgements

The work is partially supported by the Philosophy and Social Sciences Project for Colleges and Universities in Jiangsu Province (nos. 2019SJA0649), National Natural Science Foundation of China (nos. 41901174, 61503188).

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Authors and Affiliations

  1. Faculty of Hospitality and Tourism Management, Macau University of Science and Technology, Macau, 999078, China

    Fangqing Sheng & Yang Zhang

  2. School of Humanities and Arts, Jiangsu Maritime Institute, Nanjing, 211199, Jiangsu, China

    Fangqing Sheng

  3. Nanjing Vocational University of Industry Technology, Nanjing, 210023, Jiangsu, China

    Cheng Shi

  4. Institute of Quantitative and Technical Economics, Chinese Academy of Social Science, Beijing, 100732, China

    Cheng Shi

  5. College of Economics and Management, Nanjing Forestry University, Nanjing, 210037, Jiangsu, China

    Mengyuan Qiu

  6. School of Computer Science and Technology, Nanjing Normal University, Nanjing, 210023, Jiangsu, China

    Shuaizhen Yao

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  1. Fangqing Sheng
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  2. Yang Zhang
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  3. Cheng Shi
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  4. Mengyuan Qiu
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Correspondence to Yang Zhang.

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Sheng, F., Zhang, Y., Shi, C. et al. Xi’an tourism destination image analysis via deep learning. J Ambient Intell Human Comput 13, 5093–5102 (2022). https://doi.org/10.1007/s12652-020-02344-w

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