Semantic-driven watermarking of relational textual databases
作者：
Highlights：
• Mark embedding through synonyms substitutions avoids to compromise data quality.
• Controlling the number of times each mark is embedded contributes to high resiliency.
• Multi-word textual attributes in relational data helps to protect their ownership.
• Majority voting compensates lack of precision in word sense disambiguation algorithms.
摘要
•Mark embedding through synonyms substitutions avoids to compromise data quality.•Controlling the number of times each mark is embedded contributes to high resiliency.•Multi-word textual attributes in relational data helps to protect their ownership.•Majority voting compensates lack of precision in word sense disambiguation algorithms.
论文关键词：Digital watermarking,Relational databases,Semantic similarity analysis
论文评审过程：Received 6 December 2019, Revised 12 September 2020, Accepted 12 September 2020, Available online 28 September 2020, Version of Record 10 February 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2020.114013
