Improved Recommendation of Photo-Taking Locations using Virtual Ratings
Refereed Conference Meeting Proceeding
We consider the task of collaborative recommendation of photo-taking locations. We use datasets of geotagged photos. We map their locations to a location grid using a geohashing algorithm, resulting in a user × location implicit feedback matrix. Our improvements relative to previous work are twofold. First, we create virtual ratings by spreading users’ preferences to neighbouring grid locations. This makes the assumption that users have some preference for locations close to the ones in which they take their photos. These virtual ratings help overcome the discrete nature of the geohashing. Second, we normalize the implicit frequency-based ratings to a 1-5 scale using a method that has been found to be useful in music recommendation algorithms. We demonstrate the advantages of our approach with new experiments that show large increases in hit rate and related metrics.
Procs. of the Workshop on Recommenders in Tourism (Workshop Programme of the Tenth ACM Conference on Recommender Systems)
Digital Object Identifer (DOI):
National University of Ireland, Cork (UCC)
Open access repository: