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- Labeling Framework Description: The labeling framework is a structured approach to managing data labeling in machine learning projects. This process is(...) Read more
- Latent Data Description: Latent data refers to information that is not directly observable but can be inferred or derived from other data. This type of data(...) Read more
- Linkage Attack Description: Linkage attack is a technique used to re-identify anonymized data by combining different sources of information. This type of(...) Read more
- Local Differential Privacy Description: Local Differential Privacy is a privacy model that seeks to protect individuals' personal information by adding noise to the data(...) Read more
- Log File Anonymization Description: Log file anonymization is the process of removing or obscuring sensitive information from log files, which are detailed records of(...) Read more
- Longitudinal Data Description: Longitudinal data is a type of data collected over time, allowing for the observation of changes and trends in a set of variables.(...) Read more
- Label-Based Anonymization Description: Label-based anonymization is a technique that uses labels to categorize and anonymize data, allowing sensitive information to be(...) Read more
- Linear Regression Anonymization Description: Linear regression anonymization is a method that uses linear regression techniques to anonymize data, ensuring that sensitive(...) Read more
- Logical Anonymization Description: Logical anonymization is a data protection method that focuses on the logical structure of information, allowing data to be used(...) Read more
- Lemmatization Description: Lemmatization is the process of reducing words to their base or root form, known as the lemma. Unlike stemming, which cuts words(...) Read more
- Location-Based Anonymization Description: Location-based anonymization is a technique that aims to protect individuals' privacy by removing or modifying data that can(...) Read more
- Linguistic Anonymization Description: Linguistic anonymization is the process of modifying textual data in such a way that characteristics that could identify specific(...) Read more
- Laplacian Noise Description: Laplacian noise is a type of statistical perturbation added to data to protect individuals' privacy in the context of differential(...) Read more
- Least Squares Anonymization Description: Least Squares Anonymization is a statistical method used to protect data privacy by minimizing the sum of the squares of the(...) Read more
- Layered Anonymization Description: Layered anonymization is an advanced technique that applies multiple levels of anonymization to data to enhance its protection.(...) Read more
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