Simple and Scalable Response Prediction for Display Advertising
| Autor: | Eren Manavoglu, Olivier Chapelle, Romer Rosales |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
SIMPLE (military communications protocol)
business.industry Computer science Display advertising media_common.quotation_subject Hash function Feature selection Terabyte Machine learning computer.software_genre Theoretical Computer Science Core (game theory) Artificial Intelligence Scalability Conversation Artificial intelligence business computer media_common |
| Zdroj: | ACM Transactions on Intelligent Systems and Technology. 5:1-34 |
| ISSN: | 2157-6912 2157-6904 |
| DOI: | 10.1145/2532128 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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