Deep Learning for User Interest and Response Prediction in Online Display Advertising

User interest and behavior modeling is a critical step in online digital advertising. On the one hand, user interests directly impact their response and actions to the displayed advertisement (Ad). On the other hand, user interests can further help determine the probability of an Ad viewer becoming...

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Veröffentlicht in:	Data Science and Engineering Jg. 5; H. 1; S. 12 - 26
Hauptverfasser:	Gharibshah, Zhabiz, Zhu, Xingquan, Hainline, Arthur, Conway, Michael
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2020 Springer SpringerOpen
Schlagworte:	Advertising campaigns Advertising executives Algorithm Analysis and Problem Complexity Analysis Artificial Intelligence Campaign Chemistry and Earth Sciences Click prediction Computer Science Data Mining and Knowledge Discovery Database Management Deep learning Display advertising Email marketing LSTM network Machine learning Physics Statistics for Engineering Systems and Data Security New York Taiwan Deep learning Click prediction Display advertising Campaign LSTM network
ISSN:	2364-1185, 2364-1541
Online-Zugang:	Volltext
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