PBTR: Pre-training and Bidirectional Semantic Enhanced Trajectory Recovery

Author:

Zhang QimingORCID,Liao TianxiORCID,Zhu TongyuORCID,Sun LeileiORCID,Lv WeifengORCID

Publisher

Springer Nature Singapore

Reference22 articles.

1. Bahdanau, D., Cho, K., Bengio, Y.: Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473 (2014)

2. Cho, K., et al.: Learning phrase representations using RNN encoder-decoder XGBoostfor statistical machine translation. arXiv preprint arXiv:1406.1078 (2014)

3. Erhan, D., Courville, A., Bengio, Y., Vincent, P.: Why does unsupervised pre-training help deep learning? In: Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, pp. 201–208. JMLR Workshop and Conference Proceedings (2010)

4. Feng, J., et al.: DeepMove: predicting human mobility with attentional recurrent networks. In: Proceedings of the 2018 World Wide Web Conference, pp. 1459–1468 (2018)

5. Han, L., Du, B., Lin, J., Sun, L., Li, X., Peng, Y.: Multi-semantic path representation learning for travel time estimation. IEEE Trans. Intell. Transp. Syst. 23(8), 13108–13117 (2021)

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