User Trajectory

User trajectory analysis focuses on understanding and modeling the movement patterns of individuals across various contexts, aiming to extract meaningful insights from location data. Current research emphasizes the use of deep learning architectures, particularly transformers and recurrent neural networks, to analyze these trajectories for tasks like next-location prediction, user identification (trajectory-user linking), and personalized service recommendations. These advancements have implications for diverse fields, including urban planning (understanding city functionality), personalized marketing (tailoring user experiences), and security (behavior-based authentication). The development of efficient and accurate models for handling large-scale trajectory data remains a key focus.