wzhe06/Ad-papers

Papers on Computational Advertising

51
/ 100
Established

This is a curated collection of research papers and learning materials focused on computational advertising. It provides a structured overview of key algorithms and methodologies, from optimization techniques to recommendation systems. Digital marketers, advertising platform engineers, and data scientists specializing in ad tech can use this to deepen their understanding and implement advanced advertising strategies.

4,377 stars. No commits in the last 6 months.

Use this if you are an advertising professional or data scientist looking for foundational and cutting-edge research in computational advertising to improve ad relevance, targeting, and click-through rates.

Not ideal if you are looking for ready-to-use code implementations or a basic introduction to digital advertising concepts.

computational advertising ad tech digital marketing recommendation systems click-through rate prediction
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 25 / 25

How are scores calculated?

Stars

4,377

Forks

1,186

Language

Python

License

MIT

Last pushed

Feb 09, 2021

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/wzhe06/Ad-papers"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.