Google Inc.

Bahman Rabii

Yingwei Cui

Gaofeng Zhao

Wei Chai

Hui Tan

Xiaodan Song

Julie Tung

Andres S Perez-Bergquist

Jason C Miller

Yi Zhang

Kun Zhang

Mayur Dhondu Datar

Jeremiah Harmsen

Tomasz J Tunguz-Zawislak

Niyati Yagnik

Manohar Karkal Prabhu

Michael Eugene Aiello

Timothy S Lipus

Creighton Thomas

Ajay Kumar Bangla

Shilpa Arora

Megan Nance

Mike Hochberg

Jeffrey Adgate Dean

Kai Chen

Gregory Sean Corrado

Nathan Peter Lucash

Omer Gimenez Llach

Brandon Murdock Pearcy

Colin Craig McCulloch

Willa Angel Chen

William Martin Halpin, Jr

Tobias Maurer

Colin McCulloch

Gregory Joseph Badros

Yan Huang

Michael Hochberg

Claire Cui

Yingweii Cui

Dan Ardelean

A method and system for adjusting ads auction using predicted user responses to an in-ad survey is provided. The method includes (1) providing a content item associated with an actionable object, which when selected, causes a computing device to present a plurality of interactive elements each corresponding to a different one of a plurality of reasons for restricting the content item; (2) receiving, from the computing device, data indicating a particular reason, of the plurality of reasons, for restricting the content item, and the particular reason corresponding to a particular interactive element, of the plurality of interactive elements, that was selected by the user; and (3) updating, using the received data, a content selection model for selecting content items, wherein the content selection model is associated with the user.

Adjust ads auction using predicted user response to an in-ad survey

The present disclosure selects third party content based on feedback. A selector identifies several content items including first and second content items (or more) responsive to a request. A machine learning engine determines a first feature of the first content item, a second feature of the second content item, and a third feature of the web page or a device associated with the request. The machine learning engine determines, responsive to the first feature and the third feature, a first score for the first content item based on a machine learning model generated using historical signals received from devices via a metadata channel formed from an electronic feedback interface. The machine learning engine determines a second score for the second content item responsive to the second feature and the third feature. A bidding module determines a price for the first content item based on the first and second scores.

Systems and methods of evaluating information in a computer network environment are provided. A data processing system can obtain or receive a content placement criterion, such as a keyword, associated with a content item and can determine a quality metric of the content placement criterion. The data processing system can identify a candidate content placement criterion and expand placement criteria associated with the content item to include the content placement criterion and the candidate content placement criterion based at least in part on an evaluation of the quality metric of the content placement criterion. The data processing system can expand placement criteria based in part on a throttling parameter. The data processing system can identify a correlation between a document and the placement criteria to identify appropriate content items for the document.

Expansion of high performing placement criteria

Systems and methods of providing information via a computer network are provided. A data processing system can identify a cluster that includes a plurality of online content items having a semantic or user similarity. The data processing system determines a plurality of cluster placement criteria of the cluster, and receives content configured for display with a web page. The content can be associated with the cluster based on the semantic or user similarity. A cluster placement criterion of the plurality of cluster placement criteria can be selected based on a quality metric of the selected cluster placement criterion, and the selected cluster placement criterion can be provided as a supplemental criterion used to select the content for display with the web page.

Content placement criteria expansion

Method and systems for displaying content items on an information resource include identifying a supplemental content item to append to a DOM tree of the information resource and identifying a first content item displayed in a first container of the information resource. The methods also includes monitoring a position of a predetermined portion of the first content item relative to a viewport of the application and determining, responsive to monitoring the position of the predetermined portion of the first content item, that the first content item is visible within the viewport of the application. The method also includes appending the supplemental content item in a second container at a first position between the first container and an end of the information resource and displaying the supplemental content item within the viewport of the application responsive to detecting a scroll action towards the end of the information resource.

Systems and methods for dynamically appending supplemental content to an information resource responsive to scroll activity

Systems and methods for selecting third party content based on feedback

Structured data sets including one or more attributes are identified, each structured data set associated with, for example, a particular user. Values corresponding the at least one of the one or more attributes in each structured data set are identified. A condition established by a content provider, for instance, an advertiser, is compared to the identified values to determine if the condition is satisfied. When the condition is satisfied, one or more content items are identified to the users associated with the structured data sets containing identified values satisfying the condition.

User-targeted advertising

A method is provided. The method includes receiving a request for one or more ads, the request including a first identifier for a first content source, wherein a first set of content is available from the first content source, responsive to the request, determining whether a second set of content is available from a second content source, wherein the second set of content is a structured content version of the first set of content, converting the first identifier for the first content source to a second identifier for the second content source if the second set of content is available from the second content source, receiving the second set of content from the second content source using the second identifier, and selecting the one or more ads using at least some content from the second set of content from the second content source.

Structured content views of web page content

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San Francisco, CA, United States of America

Bahman Rabii