Personalized Landmark Recommendation Based on Geotags from Photo Sharing Sites

Proceedings of the International AAAI Conference on Web and Social Media, 5

Volume

Vol. 5 No. 1 (2011): Fifth International AAAI Conference on Weblogs and Social Media

Poster Papers

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.

10.1609/icwsm.v5i1.14152