Google Inc.

Arun Mathew

Sandeep Jain

Kaleigh S Smith

Per R Anderson

Jocelyn Miller

Ian Langmore

Alexander Anikul

Prashant Kumar

Systems and methods of leveraging machine learning to predict user generated content are provided. For instance, first entity data associated with an entity can be received. The first entity data can include user specified data associated with an attribute of the entity. The first entity data can be input into a machine-learned content prediction model. Inferred entity data can be received as output of the machine-learned content prediction model. The inferred entity data can include inferred data descriptive of the attribute of the entity.

Leveraging machine learning to predict user generated content

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

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New York, NY, United States of America

Arun Mathew