Discovering Personally Identifiable Information in Textual Data - A Case Study with Automated Concatenation of Embeddings

Author:

Shahriar Md Hasan,Kamal Abrar Hasin,Kayem Anne V. D. M.ORCID

Publisher

Springer Nature Switzerland

Reference37 articles.

1. Ahmad, F., et al.: A deep learning architecture for psychometric natural language processing. In: ACM Trans. Inf. Syst. 38(1) ISSn: 1046-8188 (2020). https://doi.org/10.1145/3365211 URL: https://doi.org/10.1145/3365211

2. Allen, J.F.: Natural language processing. In: Encyclopedia of Computer Science. GBR: John Wiley and Sons Ltd., pp. 1218–1222. isbn: 0470864125 (2003)

3. Cohen, W.,: Enron email dataset. carnegie mellon university, 2015. url: https://www.cs.cmu.edu/~enron. (Accessed: 8 Mar 2023)

4. Devlin, J., et al.: BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In: CoRR abs/1810.04805 (2018). arXiv: 1810.04805. URL: http://arxiv.org/abs/1810.04805

5. Dong, J.: Natural language processing pretraining language model for computer intelligent recognition technology”. In: ACM Trans. Asian Low-Resour. Lang. Inf. Process. (2023). issn: 2375-4699. https://doi.org/10.1145/3605210. URL: https://doi.org/10.1145/3605210

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