Google Inc.

Jocelyn Miller

Corinna Cortes

Sandeep Jain

Ana Radovanovic

Arun Mathew

David Tussey

Alexander Anikul

Prashant Kumar

Methods, systems, and apparatus, including computer programs encoded on a computer-readable storage medium, including a method comprising: receiving a content item request from a resource, the resource associated with a resource sponsor; verifying the content item request including filtering out spam requests and determining if the content item request is valid; for any invalid requests, providing a content item in response to the content item request that is in conformance with an existing definition provided by the resource sponsor; and presenting information related to invalid requests to the resource sponsor in a user interface, the user interface including tools for enabling the resource sponsor to automatically accept and validate a content item request so that subsequent requests of the same type are validated upon receipt.

Auto-suggested content item requests

A computer-implemented method for defining a segment based on interaction proneness includes receiving online activity data that specifies instances of presentation for one or more content items, and instances of user interaction detected for any of the content items. The method includes training at least one predictive model on the online activity data, the predictive model trained to predict interaction proneness based on one or more characteristics associated with the instances of user interaction. The method includes identifying, using the predictive model, at least one of the characteristics as being associated with the interaction proneness. The method includes generating at least one segment definition that takes into account the identified characteristic.

Defining a segment based on interaction proneness

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Hoboken, NJ, United States of America

Jocelyn Miller