A Spatial-Temporal Self-Attention Network (STSAN) for Location Prediction

Figure 1

The overall architecture of STSAN. First the feature information is extracted from the entire history of a user by feature extraction module. Then, we apply trajectory model to obtain user trajectory representation. At the end of the sequence, the hidden state of trajectory attention is passed through a softmax layer for next location prediction.