Travel Recommendation System Using Geotagged Photos

Abstract

Recently in multimedia, web services contain a huge volume of geo-tagged photos. The users who upload these photos are sharing their travel experiences through them. Geo-tagged photos have crucial information imbibed within them, like location, time, tags and weather. Travel Recommendation methods that exist do not take into consideration user preferences and weather all at once. In this paper, a travel recommendation system is proposed for tourists in Mumbai according to their preferences, weather and live events. The preferences are obtained according to the prior travel history of user(s) and recommendations are suggested. Dataset is collected from the Flickr API and the technique is examined for Mumbai, an Indian metropolitan city. The effectiveness of the proposed method can be seen from the experimental results, which shows an average of 15% improvement in the accuracy with respect to the existing methods. © 2017 Association for Computer Machinery.