Effective ad targeting with concealed profiles

In an ad targeting system, an advertiser specifies the profiles of the users to whom it is interested in showing an ad. The underlying ad distribution system would like to use profiles of users, if available, to match advertisers to users in an optimal manner. Availability of the needed profile information very much depends on whether users opt-in to have their profile information revealed. When some set of users opt-out of having their profile information revealed, possibly for privacy reasons, an ad distribution system needs methods to match advertisers to the right users despite the system itself not having full knowledge of the users' profiles. In this paper, we propose solutions to this problem thereby expanding the universe of users to whom ad targeting becomes feasible. Ads can be targeted to opt-in users, whose profiles are therefore known to the ad targeting system, using now known approaches. Our solution enables targeting of ads to users who have chosen to not opt-in to reveal their profiles. Such users keep their true interest profiles to themselves (locally on their equipment). Ads to be displayed are selected locally and ad scheduling is done using a guaranteed approximation online algorithm that uses only statistically falsified profile information and not the true profiles. Despite the use of statistically falsified information, accurate targeting can be done. We show both analytically and experimentally that the performance of the ad scheduler is quite close to optimal.