reidentificazione
Reidentificazione is a process used in data science and machine learning to determine whether an individual that appears in a dataset or dataset pairs can be identified as the same person across different time periods or datasets. This technique is commonly used in applications such as tracking individuals in video surveillance systems or analyzing changes in an individual's identity over time.
Reidentificazione is often performed using various algorithms and techniques that rely on the correlation of identifiable
The outcome of the reidentificazione process can be either a match or a non-match. If the process
The value of reidentificazione lies in its application in various domains such as marketing, insurance, healthcare,
Accuracy of the reidentificazione results can be compromised due to the presence of missing or noisy data,
Several studies have demonstrated the feasibility of reidentificazione using real-world data sets, which also serve to