Location-based social networks (LBSNs) allow users to share the locations that they have visited with others in a number of ways. LBSNs like Foursquare allow users to ‘check in’ to a location to share their locations with their friends. However, in Yelp, users can engage with the LBSN via modes other than check-ins. Specifically, Yelp allows users to write ‘tips’ and ‘reviews’ for the locations that they have visited. The geo-social correlations in LBSNs have been exploited to build systems that can recommend new locations to users. Traditionally, recommendation systems for LBSNs have leveraged check-ins to generate location recommendations. We demonstrate the impact of two new modalities - tips and reviews, on location recommendation. We propose a graph based recommendation framework which reconciles the ‘tip’ and ‘review’ space in Yelp in a complementary fashion. In the process, we define novel intra user and intra-location links leveraging tip and review information, leading to a 15% increase in precision over the existing approaches.
CITATION STYLE
Gupta, S., Pathak, S., & Mitra, B. (2015). Complementary usage of tips and reviews for location recommendation in Yelp. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9078, pp. 720–731). Springer Verlag. https://doi.org/10.1007/978-3-319-18032-8_56
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