A Framework to Predict the Advertise View Ability by using Machine Learning
Pages : 609-612
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Abstract
Advertisements assume a crucial job in each industry and they help in the development of the business. The commercials that are distributed are not seen appropriately by the client in view of inadequate scrolling. By utilizing the scroll measurement process, we can foresee the view ability of the Advertisements dependent on the scrolling rate and and also predict the maximum viewed advertisements. Online advertisement has become a billion-dollar industry, and it continues developing. Advertisers endeavor to send marketing messages to draw in potential clients by means of realistic flag promotions on distributes website pages. Promoters are charged for each perspective on a page that conveys their presentation advertisements. Notwithstanding, ongoing investigations have found that the greater part of the advertisements are never appeared on clients’ screens because of inefficient scrolling. Hence, advertisers waste a lot of cash on these promotions that don’t bring any return on investment.
Keywords: Computational Advertising, View-ability Prediction, User Behavior.