Yahoo! Inc.

Microsoft Technology Licensing, LLC

Facebook, Inc.

Christopher John Leggetter

Erick Cantu-Paz

Jan O Pedersen

Daniel R Delling

Xiang Zhao

Andrew V Goldberg

Su-Lin Wu

Ashvin Kannan

Renato F Werneck

Chad Carson

Rukmini Iyer

Pero Subasic

Shengbo Guo

James Li

Christopher C LuVogt

Lu Wang

Michael Charles Bailey

David Cho-Lun Ku

Yue Zhuo

Yixian Zhu

Xia Sharon Wan

Darshan Vishwanath Kantak

Seyoung Park

Yunhong Zhou

Naiping Liu

Grace Louise Jackson

Kristin S Hendrix

An online system receives posts that include links to various external pages and presents those posts to users of the online system. When the online system determines an opportunity to present a post to a particular viewing user of the online system, the online system determines a quality metric and an associated value score for the post. The quality metric is determined as a likelihood that the viewing user will view the external page for less than a threshold time period, and is used to adjust the associated value score. The online system compares the value score of the post to the value scores of other posts and selects one or more of the compared posts for presentation to the viewing user of the online system.

Selecting content with an external link for presentation based on user interaction with external content

Aspects of the subject disclosure are directed towards managing sponsored online content based upon advertiser behavior. Defining mini-markets to represent such advertiser behavior may be accomplished by clustering queries that generate revenue from one or more campaigns. Query revenue data between queries and a set of campaigns may be used to determine such mini-markets. To illustrate, a query whose highest revenue is attributed to a campaign may be selected for that campaign's mini-market. When that query is entered as a search term, the campaign's mini-market helps allocate space for advertisements.

System and method for internet marketing by endorsements

The present invention is directed towards systems and methods for predicting a frequency with which an advertisement displayed in response to a query will be selected. The method of the present invention comprises receiving analytics data associated with a display of one or more advertisements in response to one or more queries. One or more features associated with the one or more advertisements displayed in response to the one or more queries are identified. One or more functions are generated for predicting a frequency with which a given advertisement displayed in response to a query will be selected using the analytics data and features associated with the one or more advertisements displayed in response to the one or more queries.

System and method for generating functions to predict the clickability of advertisements

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Belmont, CA, United States of America

Christopher John Leggetter