Yahoo! Inc.

Oath Inc.

Excalibur Ip, LLC

Manugistics Inc.

Prabhakar Krishnamurthy

Jean-Marc Langlois

Bruno Fernandez Ruiz

Aharon Lavi

Scott J Gaffney

Abhay K Gupta

Xing Yi

Feng Yang

Maxim I Sviridenko

Frederick Kenneth Schmidt, Jr

Panagiotis Papadimitriou

Thomas Edward Guardino

Dean Weldon Boyd

Brian Lawrence Monteiro

Mark Cooke

Jorgen K Andersson

Chris Wilkens

Mike Gordon

Chia-Hung Charles Tai

Ruggiero Cavallo

Anupama Kolamala

Greg Cook

Mudita Purang

Ravi Nandiwada

Darja Krushevskaja

Steve Haas

Yan Jiao

Systems, devices, and methods generate a more accurate search advertising auction that considers heterogeneous attributes of advertisements for inclusions into an available advertisement space. Each advertisement considered for inclusion into the available advertisement space may be further analyzed to generate a truthful estimated price for reference during an online bidding for the advertisement space.

Local-search optimization and pricing for rich ad allocation

A method for adjusting pricing for advertisements of non-guaranteed delivery ('NDG') advertising auctions includes retrieving dwell time information for users that engage advertisements streamed to the users in a display content stream. The method aggregates the advertisements into different groups according to display context (such as advertisement category, viewing device, product in which the advertisement is streamed, etc.) and computes short-click ratios of advertisements in each group based on a short-click threshold assigned to the group and the user dwell time information for the group. The method further determines average dwell time by users on advertisements in respective groups. The method adjusts pricing of the advertisements of a group for NGD bidding based on the short-click ratio and average dwell time of the group, to favor groups having higher dwell times and lower short-click ratios. Prices may be dynamically adjusted across different contexts based on user engagement information.

User engagement-based contextually-dependent automated pricing for non-guaranteed delivery

A server system of an online information system displays advertising items and content items retrieved from storage devices as a stream viewable by a user on a user device. The advertisement items and the content items are ordered in the stream by a ranking score computed for each of the advertisement items and each of the content items. A quality scoring system determines an affinity score between a user and a present content item based on features of the present content item matching user profile parameters associated with the user and identifies post-interaction satisfaction with a prior content item. The quality scoring system determines a quality score based on the affinity score and the post-interaction satisfaction. The quality score is used for ordering items in the stream. The server system transmits a web page including the stream to a user device over a network. In this manner, advertising items and content items compete in a unified marketplace for inclusion in the stream for viewing by the end user.

Quality scoring system for advertisements and content in an online system

Techniques are provided for identifying topics that are unassociated with a dominant URL. A set of keywords associated with a topic is identified. A search log is scanned to identify search queries associated with the set of keywords. The identified search queries are grouped into clusters. Clusters associated with similar URLs are merged to generate an extended seed query string. The extended seed query string is analyzed to determine whether it relates to an existing dominant URL. If the extended seed query string is determined to be unassociated with an existing dominant URL, a web page associated with the topic may be generated.

Method and system for generating web pages for topics unassociated with a dominant URL

A server system of an online information system displays advertising items and content items retrieved from storage devices as a stream viewable by a user on a user device. The advertisement items and the content items are ordered in the stream by a ranking score computed for each of the advertisement items and each of the content items. The server system transmits a web page including the stream to a user device over a network. In this manner, advertising items and content items compete in a unified marketplace for inclusion in the stream for viewing by the end user.

Unified marketplace for advertisements and content in an online system

A business process and computer system known as the 'Target Pricing System' (TPS) that generates an optimum bid or value for a competitively bid good or service. The system is resident on one or more host processors in connection with one or more data stores, and includes a product model that defines list values for the bid using stored price data and costs the values using stored cost data, a competitor net price model that calculates an equivalent competitor net price for the value, and

Target pricing system

Growing community of inventors

Pleasanton, CA, United States of America

Prabhakar Krishnamurthy