JSAI2024

Presentation information

International Session

International Session » IS-2 Machine learning

[3Q1-IS-2a] Machine learning

Thu. May 30, 2024 9:00 AM - 10:40 AM Room Q (Room 402)

Chair: Takahiro Uchiya (Nagoya Institute of Technology)

10:20 AM - 10:40 AM

[3Q1-IS-2a-05] Predicting Performance of Responsive Search Ad Surface Texts

〇Melvin Charles Dy1 (1. OPT, Inc.)

[[Online]]

Keywords:Machine Learning, Advertising

Despite the popularity of responsive ads that dynamically combine text assets to best suit individual search queries, there is a distinct need for predicting how the final displayed text might perform. In order to serve those needs, we are building a model that leverages the impressions of responsive search ad permutations and aggregate CTRs of the responsive ads they belong to. This paper describes the thinking and assumptions behind this system as well as some of the challenges involved.

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