Summary of A Different Level Text Protection Mechanism with Differential Privacy, by Qingwen Fu
A Different Level Text Protection Mechanism With Differential Privacy
by Qingwen Fu
First submitted to arxiv on: 5 Sep 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed method leverages the BERT pre-training model to extract words of varying degrees of importance, demonstrating its efficacy in real-world applications. By analyzing the perturbation results for words with distinct levels of importance, researchers show that this approach can significantly impact overall text utility, making it a valuable tool for long text protection. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper introduces a new method using BERT to identify important words in texts. This helps make longer texts easier to protect from changes. The study shows how well the method works and its effects on text usefulness. |
Keywords
» Artificial intelligence » Bert
