Abstract
We investigate a new graphical model that can generate latent abstract concepts of venues, or Point of Interest (POI) by exploiting text data in venue profiles obtained from location-based social networks (LBSNs). Our model offers tailor-made modeling for two different types of text data that commonly appears in venue profiles, namely, tags and comments. Such modeling can effectively exploit their different characteristics. Meanwhile, the modeling of these two parts are tied with each other in a coordinated manner. Experimental results show that our model can generate better abstract venue concepts than comparative models.
The work described in this paper is substantially supported by grants from the Research Grant Council of the Hong Kong Special Administrative Region, China (Project Codes: 413510 and 14203414) and the Microsoft Research Asia Urban Informatics Grant FY14-RES-Sponsor-057. This work is also affiliated with the CUHK MoE-Microsoft Key Laboratory of Human-centric Computing and Interface Technologies.
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Liao, Y., Jameel, S., Lam, W., Xie, X. (2015). Abstract Venue Concept Detection from Location-Based Social Networks. In: Zuccon, G., Geva, S., Joho, H., Scholer, F., Sun, A., Zhang, P. (eds) Information Retrieval Technology. AIRS 2015. Lecture Notes in Computer Science(), vol 9460. Springer, Cham. https://doi.org/10.1007/978-3-319-28940-3_12
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