@article{Shi_Serdyukov_Hanjalic_Larson_2021, title={Personalized Landmark Recommendation Based on Geotags from Photo Sharing Sites}, volume={5}, url={https://ojs.aaai.org/index.php/ICWSM/article/view/14152}, DOI={10.1609/icwsm.v5i1.14152}, abstractNote={ <p> 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&rsquo; 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. </p> }, number={1}, journal={Proceedings of the International AAAI Conference on Web and Social Media}, author={Shi, Yue and Serdyukov, Pavel and Hanjalic, Alan and Larson, Martha}, year={2021}, month={Aug.}, pages={622-625} }