Get the free Achieving Anonymity via Clustering Gagan Aggarwal1 Google Inc - theory stanford
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Achieving Anonymity via Clustering Pagan Aggarwal1 Google Inc. Mountain View, CA 94043 Tomas Feder2 Comp. Sc. Dept. Stanford University Stanford, CA 94305 Krishna ram Kenthapadi2 Comp. Sc. Dept. Stanford
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What is achieving anonymity via clustering?
Achieving anonymity via clustering is a technique used to protect the identity of individuals by grouping them together in clusters. This helps to hide individual information and make it difficult to identify specific individuals within the dataset.
Who is required to file achieving anonymity via clustering?
The organization or entity responsible for managing and processing the data is required to implement achieving anonymity via clustering.
How to fill out achieving anonymity via clustering?
To fill out achieving anonymity via clustering, the organization needs to apply clustering algorithms or techniques to the data in order to group individuals together.
What is the purpose of achieving anonymity via clustering?
The purpose of achieving anonymity via clustering is to protect the privacy and confidentiality of individuals' information by making it difficult to identify specific individuals within the dataset.
What information must be reported on achieving anonymity via clustering?
The information that must be reported on achieving anonymity via clustering includes details about the clustering techniques used, the number of clusters formed, and any additional privacy measures implemented.
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