The DOI matches its Crossref record; 58 of the 58 references it cites were found in a registry or an index.
Simple and Scalable Response Prediction for Display Advertising
Abstract
Clickthrough and conversation rates estimation are two core predictions tasks in display advertising. We present in this article a machine learning framework based on logistic regression that is specifically designed to tackle the specifics of display advertising. The resulting system has the following characteristics: It is easy to implement and deploy, it is highly scalable (we have trained it on terabytes of data), and it provides models with state-of-the-art accuracy.
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Cited by
Deep & Cross Network for Ad Click Predictions
Wang, R., Fu, B., Fu, G., & Wang, M. (2017) · Proceedings of the ADKDD'17 · doi:10.1145/3124749.3124754 · Cited by 1,161
CatBoost: unbiased boosting with categorical features
Prokhorenkova, L., Gusev, G., Vorobev, A., Dorogush, A. V., & Gulin, A. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1706.09516 · Cited by 1,110
Identifying machine learning techniques for classification of target advertising
Choi, J.-A., & Lim, K. (2020) · ICT Express · doi:10.1016/j.icte.2020.04.012 · Cited by 139
Yu, C., Zhang, Z., Lin, C., & Wu, Y. J. (2020) · Industrial Marketing Management · doi:10.1016/j.indmarman.2019.05.001 · Cited by 124
Automatic ad format selection via contextual bandits
Tang, L., Rosales, R., Singh, A., & Agarwal, D. (2013) · Proceedings of the 22nd ACM international conference on Information & Knowledge Management · doi:10.1145/2505515.2514700 · Cited by 111
Self-citation
Metadata
- Authors
- Chapelle, O., Manavoglu, E., & Rosales, R.
- Venue
- ACM Transactions on Intelligent Systems and Technology
- Published
- 2014-12-29
- Volume
- 5
- Issue
- 4
- Pages
- 1-34
- ISSN
- 2157-6904 (ISSN-L)
- 2157-6912
- OpenAlex
- W1985759455
- Cited by
- 318
- References
- 58
- FWCI
- 68.42
- Type
- journal article
- Language
- en
- Open access
- closed
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