Recommending Tours and Places-of-Interest based on User Interests from Geo-tagged Photos

This is the authors' abstract. We don't add key points for this paper.

Photo sharing sites like Flickr and Instagram have grown increasingly popular in recent years, resulting in a large amount of uploaded photos. In addition, these photos contain useful meta-data such as the taken time and geo-location. Using such geo-tagged photos and Wikipedia, we propose an approach for recommending tours based on user interests from his/her visit history. We evaluate our proposed approach on a Flickr dataset comprising three cities and find that our approach is able to recommend tours that are more popular and comprise more places/points-of-interest, compared to various baselines. More importantly, we find that our recommended tours reflect the ground truth of real-life tours taken by users, based on measures of recall, precision and F1-score.