The Rubicon Project, Inc.

Duc Chau

Julie Mattern

Matt Meyer

Eric Jamieson

David Williams

Hongguang Bi

A system reducing the number of default ads displayed by a user agent thereby maximizing revenue for webpage publishers. To maximize revenue, the system manages multiple ad networks so that webpage publishers can have access to advertisements from the multiple ad networks. Typically, when an ad network serves a default ad, the system queries the next ad network. If the next ad network serves a non-default ad, then the ad is served. Otherwise, the system selects another ad network until either a non-default ad is served or a specific period of time elapses or a maximum number of ad networks have been queried, in which case the default ad is served. Ad networks may be ranked by revenue generation and/or the probability of serving a default ad. Inquiries to ad networks may be biased according to such rankings.

Ad matching system and method thereof

A system and method for determining inappropriate content within images. A plurality of training images are used to teach the machine. The training images are converted into numerical data and stored along with its human judged label in a BigMatrix. Through the BigMatrix, a RandomForest is created to discern patterns among the training images and human-judged labels. To determine whether an image contains inappropriate content, the image is converted into numerical data. The numerical data is fed to the RandomForest generated from the plurality of training images and known content. The numerical data is fed down each tree within the RandomForest. When the numerical data is routed down through the branches of the trees and terminated at a leaf node, a vote for the leaf node is obtained. The overall response of the RandomForest is given by a majority rules vote for each tree within the RandomForest.

Growing community of inventors

San Pedro, CA, United States of America

Duc Chau