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A Spatial-Temporal Self-Attention Network (STSAN) for Location Prediction
2021
Complexity
With the popularity of location-based social networks, location prediction has become an important task and has gained significant attention in recent years. However, how to use massive trajectory data and spatial-temporal context information effectively to mine the user's mobility pattern and predict the users' next location is still unresolved. In this paper, we propose a novel network named STSAN (spatial-temporal self-attention network), which can integrate spatial-temporal information with
doi:10.1155/2021/6692313
fatcat:czjc7nfi6bakdlh3zdvcnbc6a4