@article{3387,
  keywords = {Destination Image, Deep Learning, Natural Language Processing, Destination Marketing Organization, Scene Recognition},
  author = {Angel Diaz-Pacheco and Miguel A. Álvarez-Carmona and Ansel Y. Rodríguez-González and Hugo Carlos and Ramón Aranda},
  title = {Measuring the Difference Between Pictures From Controlled and Uncontrolled Sources to Promote a Destination. A Deep Learning Approach},
  abstract = {Promoting a destination is a major task for Destination Marketing Organizations (DMOs). Although DMOs control, to some extent, the information presented to travelers (controlled sources), there are other different sources of information (uncontrolled sources) that could project an unfavorable image of the destination. Measuring differences between information sources would help design strategies to mitigate negative factors. In this way, we propose a deep learning-based approach to automatically measure the changes between images from controlled and uncontrolled information sources. Our approach exempts experts from the time-consuming task of assessing enormous quantities of pictures to track changes. To our best knowledge, this work is the first work that focuses on this issue using technological paradigms. Notwithstanding this, our approach paves novel pathways to acquire strategic insights that can be harnessed for the augmentation of destination development, the refinement of recommendation systems, the analysis of online travel reviews, and myriad other pertinent domains.},
  year = {9998},
  journal = {International Journal of Interactive Multimedia and Artificial Intelligence},
  volume = {In press},
  chapter = {1},
  number = {In press},
  pages = {1-14},
  month = {10/2023},
  issn = {1989-1660},
  url = {https://www.ijimai.org/journal/sites/default/files/2023-10/ip2023_10_003_0.pdf},
  doi = {10.9781/ijimai.2023.10.003},
}