Quantcast Corporation

Sean Huang

Eunsu Ryu

Tong T Pham

Joshua A Job

A device's location and an identifier corresponding to the device are received. The device's location is privatized by mapping it to landmarks proximate to the device's location, storing the proximate landmarks in association with the device's identifier, and discarding the received location data. The proximate landmarks are featurized to generate a model which is used to determine a value of the advertising opportunity corresponding to a target identifier.

Privacy-safe frequency distribution of geo-features for mobile devices

A mobile device's location and an identifier corresponding to the mobile device is received. The mobile device's location is privatized by mapping it to landmarks proximate to the mobile device's location, storing the proximate landmarks in association with the mobile device's identifier, and discarding the received location data. The proximate landmarks are featurized to generate a model which is used to determine a value of the advertising opportunity corresponding to a target identifier.

A mobile device's location and identifier corresponding to the mobile device is received. The mobile device's location is mapped to a plurality of landmarks proximate to the mobile device's location. The proximate landmarks are stored in association with the mobile device's identifier in a geo data store, and the received location data is then discarded. These steps are iterated over time to build up a data store that can be represented as a frequency distribution of the landmarks that surround mobile devices. Such a frequency distribution can be built for each of a plurality of mobile devices, without maintaining records of any mobile device's location.

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San Francisco, CA, United States of America

Sean Huang