Personalized Landmark Recommendation Based on Geotags from Photo Sharing Sites

Authors

  • Yue Shi Delft University of Technology
  • Pavel Serdyukov Yandex
  • Alan Hanjalic Delft University of Technology
  • Martha Larson Delft University of Technology

Abstract

Geotagged photos of users on social media sites provide abundant location-based data, which can be exploited for various location-based services, such as travel recommendation. In this paper, we propose a novel approach to a new application, i.e., personalized landmark recommendation based on users’ geotagged photos. We formulate the landmark recommendation task as a collaborative filtering problem, for which we propose a category-regularized matrix factorization approach that integrates both user-landmark preference and category-based landmark similarity. We collected geotagged photos from Flickr and landmark categories from Wikipedia for our experiments. Our experimental results demonstrate that the proposed approach outperforms popularity-based landmark recommendation and a basic matrix factorization approach in recommending personalized landmarks that are less visited by the population as a whole.

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Published

2021-08-03

How to Cite

Shi, Y., Serdyukov, P., Hanjalic, A., & Larson, M. (2021). Personalized Landmark Recommendation Based on Geotags from Photo Sharing Sites. Proceedings of the International AAAI Conference on Web and Social Media, 5(1), 622-625. Retrieved from https://ojs.aaai.org/index.php/ICWSM/article/view/14152