A semantics-maintained differential privacy protection for high-utility text

Key Points

• High-utility text can be achieved with differential privacy methods that maintain semantic meaning, enhancing data usefulness.
• Findings indicate that incorporating semantic preservation into privacy protection algorithms improves overall text utility.
• Observational analysis across various datasets shows that privacy protections can effectively balance utility and confidentiality requirements.
• This approach may enable the development of more robust data anonymization strategies but requires further exploration.