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The value of machine learning in privacy

Date of publication: November 11, 2018

Catalogue: Fusion 2018 (Big Data World + Global Qualitative)

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Authors: Carlos Ochoa, Ezequiel Paura

Abstract:

Online behavioral data is a valuable source of insights for researchers. However, data collected passively via tracking meters contains Personal Identifiable Information (PII). With the GDPR into force, the value of online behavioral data is constrained by the risk of disclosing PII. We present a machine-learning solution that significantly reduces the risk of revealing PII when sharing browsing data.

Carlos Ochoa

Author

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Ezequiel Paura

Author

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The value of machine learning in privacy

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Ochoa and Paura (2018a, November 11). The value of machine learning in privacy. ANA - ESOMAR. Retrieved April 19, 2024, from


https://ana.esomar.org/documents/the-value-of-machine-learning-in-privacy


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The value of machine learning in privacy

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Ochoa and Frattini (2018a, December 13). The value of machine learning in privacy. ANA - ESOMAR. Retrieved April 19, 2024, from


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Citation

Ochoa and Paura (2018a, November 11). The value of machine learning in privacy. ANA - ESOMAR. Retrieved April 19, 2024, from


https://ana.esomar.org/documents/machine-learning-and-privacy-10847