CTR prediction of internet ads using artificial organic networks
Corporación Universidad de la Costa
For advertising networks to increase their revenues, priority must be given to the most profitable ads. The most important factor in the profitability of an ad is the click-through-rate (CTR) which is the probability that a user will click on the ad on a Web page. To predict the CTR, a number of supervised rating models have been trained and their performance is compared to artificial organic networks (AON). The conclusion is that these networks are a good solution to predict the CTR of an ad.
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