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Zhuang, Chenyi; Ma, Qiang; Yoshikawa, Masatoshi (2015)
Publisher: Association for Computing Machinery, Inc. (ACM)
Journal: GIS '15: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems
Languages: English
Types: Conference object
Subjects: User profiling, Location familiarity, Geo-tagged image, Probabilistic model, Social network
In this paper, we propose and compare three ways of modeling photographers' location familiarity: a social network driven model, a time driven model and a location driven model. Then, the integration of the three models is further discussed. Experimental evaluations and analysis on a real data set consisting of 14, 112 images collected from three cities well demonstrate the performance of the proposed classification methods. Many applications could benefit from information about the location familiarity, such as personalized geo-social recommendation, epidemic dispersion, urban computing, and so on.
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