Address Search Correction Using Deep Learning
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-37963-5_43
Reference10 articles.
1. Bahdanau, D., Cho, K., Bengio, Y.: Neural machine translation by jointly learning to align and translate (2014). https://doi.org/10.48550/ARXIV.1409.0473. https://arxiv.org/abs/1409.0473
2. Bui, H.N., Tran, V.T.: A novel conditional random fields aided fuzzy matching in Vietnamese address standardization. In: Proceedings of the Tenth International Symposium on Information and Communication Technology, SoICT 2019, pp. 23–28. Association for Computing Machinery, New York (2019). https://doi.org/10.1145/3368926.3369687
3. Cao, H.N., Tran, V.T.: Deep neural network based learning to rank for address standardization. In: 2021 RIVF International Conference on Computing and Communication Technologies (RIVF), pp. 1–6 (2021). https://doi.org/10.1109/RIVF51545.2021.9642079
4. Cho, K., van Merrienboer, B., Bahdanau, D., Bengio, Y.: On the properties of neural machine translation: encoder-decoder approaches (2014). https://doi.org/10.48550/ARXIV.1409.1259. https://arxiv.org/abs/1409.1259
5. Christen, P., Belacic, D.: Automated probabilistic address standardisation and verification. In: Australasian Data Mining Conference (AusDM 2005) (2005)
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