出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：In digital advertising, Click-Through Rate (CTR) and Conversion Rate (CVR) are very
important metrics for evaluating ad performance. As a result, ad event prediction systems are
vital and widely used for sponsored search and display advertising as well as Real-Time
Bidding (RTB). In this work, we introduce an enhanced method for ad event prediction (i.e.
clicks, conversions) by proposing a new efficient feature engineering approach. A large realworld
event-based dataset of a running marketing campaign is used to evaluate the efficiency of
the proposed prediction algorithm. The results illustrate the benefits of the proposed ad event
prediction approach, which significantly outperforms the alternative ones.
