Field-weighted Factorization Machines for Click-Through Rate Prediction in Display Advertising-Reference-Cited by-同舟云学术

Field-weighted Factorization Machines for Click-Through Rate Prediction in Display Advertising

Published:2018 Issue: Volume: Page:
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Container-title:Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18
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Author:

Pan Junwei¹,Xu Jian²,Ruiz Alfonso Lobos³,Zhao Wenliang¹,Pan Shengjun¹,Sun Yu⁴,Lu Quan⁵

Affiliation:

1. Oath Inc., Sunnyvale, CA, USA

2. TouchPal Inc., Shanghai, China

3. University of California, Berkeley, Berkeley, CA, USA

4. LinkedIn Corporation, Mountain View, CA, USA

5. Ablibaba Group, Hangzhou, China

Publisher

ACM Press

Reference26 articles.

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5. Heng-Tze Cheng, Levent Koc, Jeremiah Harmsen, Tal Shaked, Tushar Chandra, Hrishi Aradhye, Glen Anderson, Greg Corrado, Wei Chai, Mustafa Ispir, et almbox. . 2016. Wide & deep learning for recommender systems. In Proceedings of the 1st Workshop on Deep Learning for Recommender Systems. ACM, 7--10.

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