A click-through rate prediction model and its applications to sponsored search advertising

Ad click-through rate (CTR) prediction is to estimate CTR with click log, which is influenced by the page information, the position, the user properties, the nature features of ad and some other factors. The right ads for the query and the order they are displayed greatly affects the revenue the company receives from these ads. Therefore, it is important to be able to estimating CTR precisely with click log in sponsored search advertising system. We present a useful CTR prediction model for ads of abundant history data. We also show that using our model improves the performance of an advertising system.