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Federated Learning for Privacy-Preserving Ad Targeting

The Ad Tech Blog

In the evolving landscape of digital advertising, federated learning offers a promising solution for privacy-preserving ad targeting. Ad tech companies can use it to create effective ad-targeting models. Ad tech companies face the challenge of balancing effective ad targeting with user privacy.

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The Problems With Behavioral Targeting

Brid.tv

Although it is still one of the most common advertising methods, advertisers are actively looking for alternatives to behavioral targeting (such as contextual, semantic, permission-based, and so on). Secondly, behavioral targeting seems to have missed the mark on making advertisements “less annoying” for the consumer.

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How Publishers Can Make More Money With AdTech

Clearcode

Some of the most common AdTech solutions for publishers include header bidding, self-serve ad platforms, customer data platforms (CDPs) and demand-path optimization (DPO). Managing first- and third-party data and using it for content personalization and ad targeting. Source: Clearcode.cc

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The Evolution of Google’s Privacy Sandbox

Clearcode

FLoC Criticized and Replaced by Topics API On January 14, 2020, Chrome published an intention to implement a Federated Learning of Cohorts (FLoC) API , the original solution designed for ad targeting in the Privacy Sandbox. The Electronic Frontier Foundation (EFF) also criticized FLoC , calling it a breach of user trust.

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