System and method for improving conversion rate prediction via self-supervised pretraining in online advertising

A machine readable and non-transitory medium having information recorded thereon, wherein the information, when read by the machine, causes the machine to perform the following steps:

• receiving bids directed to a display ad opportunity, wherein each of the bids includes a candidate advertisement and the display ad opportunity involves a user and an associated context;
• obtaining auxiliary features with respect to each of the bids based on a code generated by an autoencoder for the bid;
• predicting, via an enriched performance prediction model, a predicted performance metric for the candidate advertisement in each of the bids based on the auxiliary features associated with the candidate advertisement;
• and
• selecting the winning advertisement from candidate advertisements of the bids according to a ranking determined based on the respective predicted performance metrics of the candidate advertisements.

A system, comprising:

• a performance prediction unit implemented by a processor and configured for
• receiving bids directed to a display ad opportunity, wherein each of the bids includes a candidate advertisement and the display ad opportunity involves a user and an associated context, and
• predicting, via an enriched performance prediction model, a predicted performance metric for the candidate advertisement in each of the bids based on auxiliary features with respect to each of the bids based on a code generated by an autoencoder for the bid associated with the candidate advertisement;
• and
• a winning ad selection unit implemented by a processor and configured for selecting the winning advertisement from candidate advertisements of the bids according to a ranking determined based on the respective predicted performance metrics of the candidate advertisements.