18:20 〜 18:40
[1U5-IS-2b-05] Predicting CTR of Responsive Search Ads Using Handcrafted Features
[[Online, Regular]]
キーワード:Machine Learning, Feature Engineering, Advertising
In this paper, I demonstrate that a reasonably sized set of handcrafted features (866, applied to titles and description texts separately) plus encoded metadata can be used to predict the click-through rates of the dynamic Responsive Search Ad format, exceeding the performance of some fine-tuned Transformer-based large language models at a fraction of the training cost.
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