Patent ID: 9245280
Filing Date: 2016-01-26
CPC Classification: G06Q

Claim Text:
1. A method for predicting effectiveness of video advertising, the method comprising: sending videos to one or more client devices, wherein video ads are sent to the one or more client devices and viewed during ad slots in the videos by one or more users during the playing of the videos; identifying, by a computing device, attributes of a set of previously viewed video ads by automatically analyzing video data of the set of previously viewed video ads, wherein the set of previously viewed ads are from the video ads played in the ad slots; measuring, by the computing device, a video ad metric for the set of previously viewed video ads based on data received in response to the sending of the set of previously viewed video ads to the one or more client devices; generating, by the computing device, a machine learning algorithm to predict the video ad metric for new video ads using the attributes of the set of previously viewed video ads and the measured video ad metric for the set of previously viewed video ads; identifying, by the computing device, attributes of a new video ad by automatically analyzing video data in the new video ad using an attribute identification algorithm; using, by the computing device, the machine learning algorithm to determine correlation coefficients for features of the set of previously viewed video ads, wherein the features represent different combinations of the attributes, and wherein the machine learning algorithm comprises: where and where ŷ inputting, by the computing device, the features of the new video ad into the machine learning algorithm to estimate the predicted video advertising metric of the new video ad based on the correlation coefficients and the features of the new video ad.