Personalized Travel Direction Recommendation Using Social Media Photos

Authors

  • R Teja Department of CSE, Annamacharya Institute of Technology and Sciences, Kadapa, Andhra Pradesh, India
  • T Manasa Department of CSE, Annamacharya Institute of Technology and Sciences, Kadapa, Andhra Pradesh, India
  • S Sai Gopi Department of CSE, Annamacharya Institute of Technology and Sciences, Kadapa, Andhra Pradesh, India
  • S Prasanth Kumar Department of CSE, Annamacharya Institute of Technology and Sciences, Kadapa, Andhra Pradesh, India
  • C Nikitha Department of CSE, Annamacharya Institute of Technology and Sciences, Kadapa, Andhra Pradesh, India

DOI:

https://doi.org/10.5281/zenodo.15267934

Keywords:

Travel recommendation, time sensitivity, personalization, social media, recommendation model

Abstract

A travel recommendation system based on social media activity provides a customized place of interest to accommodate user-specific needs and preferences. In general, the user’s inclination towards travel destinations is subject to change over time. In this project, we have analyzed users’ twitter data, as well as their friends and followers in a timely fashion to understand recent travel interest. A machine learning classifier identifies tweets relevant to travel. The travel tweets are then used to obtain personalized travel recommendations. Unlike most of the personalized recommendation systems, our proposed model takes into account a user’s most recent interest by incorporating time-sensitive recency weight into the model. Our proposed model has outperformed the existing personalized place of interest recommendation model, and the overall accuracy is 75.23%

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Published

2025-04-23

How to Cite

R Teja, T Manasa, S Sai Gopi, S Prasanth Kumar, & C Nikitha. (2025). Personalized Travel Direction Recommendation Using Social Media Photos. International Journal of Human Computations & Intelligence, 4(3), 476–486. https://doi.org/10.5281/zenodo.15267934