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Simple and Scalable Response Prediction for Display Advertising
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- Olivier Chapelle
- Criteo
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- Eren Manavoglu
- Microsoft
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- Romer Rosales
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Description
<jats:p>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.</jats:p>
Journal
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- ACM Transactions on Intelligent Systems and Technology
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ACM Transactions on Intelligent Systems and Technology 5 (4), 1-34, 2014-12-29
Association for Computing Machinery (ACM)
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Details 詳細情報について
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- CRID
- 1361137046254629120
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- DOI
- 10.1145/2532128
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- ISSN
- 21576912
- 21576904
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- Data Source
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- Crossref