criteo
Datasets
All datasets matching “criteo”CriteoClickLogs
📊 Criteo 1TB Click Logs Dataset
This dataset contains feature values and click feedback for millions of display ads. Its primary purpose is to benchmark algorithms for clickthrough rate (CTR) prediction.
It is similar, but larger than the dataset released for the Display Advertising Challenge hosted by Kaggle:🔗 Kaggle Criteo Display Advertising Challenge
📁 Full Description
This dataset contains 24 files, each corresponding to one day of data.
🏗️… See the full description on the dataset page: https://huggingface.co/datasets/criteo/CriteoClickLogs.CriteoPrivateAd
Dataset Documentation
Private Bidding Optimisation {#private-conversion-optimisation}
The advertising industry lacks a common benchmark to assess the privacy
/ utility trade-off in private advertising systems. To fill this gap, we
are open-sourcing CriteoPrivateAds, the largest real-world anonymised
bidding dataset, in terms of number of features. This dataset enables
engineers and researchers to:
assess the impact of removing cross-domain user signals,
highlighting the… See the full description on the dataset page: https://huggingface.co/datasets/criteo/CriteoPrivateAd.CriteoPrivateAd
Dataset Documentation
Private Bidding Optimisation {#private-conversion-optimisation}
The advertising industry lacks a common benchmark to assess the privacy
/ utility trade-off in private advertising systems. To fill this gap, we
are open-sourcing CriteoPrivateAds, the largest real-world anonymised
bidding dataset, in terms of number of features. This dataset enables
engineers and researchers to:
assess the impact of removing cross-domain user signals,
highlighting the… See the full description on the dataset page: https://huggingface.co/datasets/yzhang23/CriteoPrivateAd.criteo-attribution-dataset
Criteo Attribution Modeling for Bidding Dataset
This dataset is released along with the paper:
Attribution Modeling Increases Efficiency of Bidding in Display Advertising
Eustache Diemert*, Julien Meynet* (Criteo Research), Damien Lefortier (Facebook), Pierre Galland (Criteo) *authors contributed equally
2017 AdKDD & TargetAd Workshop, in conjunction with The 23rd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2017)
When using this dataset, please cite the paper… See the full description on the dataset page: https://huggingface.co/datasets/criteo/criteo-attribution-dataset.criteocriteo-uplift
Introduction
This dataset is released along with the paper:
A Large Scale Benchmark for Uplift Modeling
Eustache Diemert, Artem Betlei, Christophe Renaudin; (Criteo AI Lab), Massih-Reza Amini (LIG, Grenoble INP)
This work was published in: AdKDD 2018 Workshop, in conjunction with KDD 2018.
When using this dataset, please cite the paper with following bibtex:
@inproceedings{Diemert2018,
author = {{Diemert Eustache, Betlei Artem} and Renaudin, Christophe and Massih-Reza, Amini}… See the full description on the dataset page: https://huggingface.co/datasets/criteo/criteo-uplift.