A context-aware personalized travel recommendation system based on geotagged social media data mining

Citation

Majid A, Chen L, Chen G, Mirza HT, Hussain I & Woodward J (2013) A context-aware personalized travel recommendation system based on geotagged social media data mining. International Journal of Geographical Information Science, 27 (4), pp. 662-684. https://doi.org/10.1080/13658816.2012.696649

Abstract
The proliferation of digital cameras and the growing practice of online photo sharing using social media sites such as Flickr have resulted in huge volumes of geotagged photos available on the Web. Based on users' traveling preferences elicited from their travel experiences exposed on social media sites by sharing geotagged photos, we propose a new method for recommending tourist locations that are relevant to users (i.e., personalization) in the given context (i.e., context awareness). We obtain user-specific travel preferences from his/her travel history in one city and use these to recommend tourist locations in another city. Our technique is illustrated on a sample of publicly available Flickr dataset containing photos taken in various cities of China. Results show that our context-aware personalized method is able to predict tourists' preferences in a new or unknown city more precisely and generate better recommendations compared to other state-of-the-art landmark recommendation methods.

Keywords
spatiotemporal data mining; geographical gazetteer; trip planning; context-aware query; geo-referenced photographs

Journal
International Journal of Geographical Information Science: Volume 27, Issue 4