Find me if you can: improving geographical prediction with social and spatial proximity
Proceedings of the 19th international conference on World wide web
Travel route recommendation using geotags in photo sharing sites
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Finding your friends and following them to where you are
Proceedings of the fifth ACM international conference on Web search and data mining
Personalized point-of-interest recommendation by mining users' preference transition
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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Twitter and Foursquare are two well-connected platforms for sharing information where growing numbers of users post location-related messages. In contrast to the longitude-latitude geotags commonly used online, e.g., on photos and tweets, new place-tags containing category information show more human-readable high-level information rather than a pair of coordinates. This grants an opportunity for better understanding users' physical locations which can be used as context to facilitate other applications, e.g., location context-aware advertisement. In this paper, we verify the assumption that users' current trails contain cues of their future routes. The results from the preliminary experiments show promising performance of a basic Markov Chain-based model.