New Proposal: Evaluation of Cohort assignment algorithms for the FLoC API

Hello W3C Web Advertising Group,

Google Research & Ads team added a new proposal to the github repository
regarding evaluation of Cohort assignment algorithms for the FLoC API.

[Coincise version
<https://github.com/google/ads-privacy/blob/master/proposals/FLoC/README.md>
, Detailed White paper
<https://github.com/google/ads-privacy/raw/master/proposals/FLoC/FLOC-Whitepaper-Google.pdf>
]

[Introduction copied from the White paper]

"The Federated Learning of Cohorts (FLoC) API is a privacy preserving
mechanism proposed within the Chrome Privacy Sandbox, for enabling interest
based advertising. The API is based on the notion of cohorts - groups of
users with similar interests. In this paper we evaluate different methods
for generating cohorts, showing clear trade-offs between privacy and
utility. Using proprietary conversion data, we demonstrate that generating
cohorts based on common interests can significantly improve quality over
random user groupings. In fact, we achieve a 350% improvement in recall and
70% improvement in precision at very high anonymity levels compared to
random user grouping. "

We hope to start to dialog with the broader group on how to improve and
evaluate cohort assignment algorithms.

Thanks,

Deepak Ravichandran

Software Engineer

Google Display Ads