ACM Transactions on Intelligent Systems and Technology (TIST): Volume 8 Issue 5, September 2017
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During the past few years, the analysis of data generated from Location-Based Social Networks (LBSNs) have aided in the identification of urban patterns, understanding activity behaviours in urban areas, as well as producing novel recommender systems that facilitate users’ choices. Recognizing crowd-mobility patterns in cities is very important for public ...
Crowd patterns, urban computing, urban mobility, smart cities