… is challenging and complex because of the spatiotemporal dynamics of movement behavior
… spatiotemporal travel patterns. We propose a deep-learning-based urban mobility prediction …

… Urban mobility pattern recognition has great … and predicting and managing traffic demand.
This paper aims to propose a data-driven method to identify metro passenger mobility patterns …

… To extract spatiotemporal prediction patterns for large networks, we propose
unsupervised learning methods such as the k-means clustering and the principal component …

… the human mobility patterns. In this paper, we focus on the human mobility prediction in the
… There are several popular mobility prediction approaches in the literature. One approach is …

… subway fare card transactions to characterize and model urban mobility patterns. We
present a simple mobility model for predicting peoples’ visited locations using the popularity of …

… -term pattern subsequently. Finally, we use a Recurrent Neural Network (RNN) to predict
future trajectories by integrating current trajectories and long short-term patterns. Experiments …

… Despite the volume of mobile cellular traffic data, we have limited knowledge on its spatio-temporal
patterns at urban scale. Tremendous records of cellular traffic collected at cell towers …

… is proposed to capture the visits with spatiotemporal periodicity by focusing on a detail …
patterns from a user’s past visiting behaviors and predict the next places based on the patterns. …

… to characterize human mobility patterns from various aspects, such as predicting human …
the spatiotemporal patterns of human convergence and divergence using a big mobile phone …

… options available, we select the ones that have been already proved successful for
spatiotemporal prediction by published works [11, 21]. The starting time at a ZOI and the total spent …