Peng Liu, Chao Wang

eBook, ePUB

Computational Advertising (eBook, ePUB)

Market and Technologies for Internet Commercial Monetization

Beschreibung

This book introduces computational advertising, and advertising monetization. It provides a macroscopic understanding of how consumer products in the Internet era push user experience and monetization to the limit.

Technische Details

• Geräte: eReader
• mit Kopierschutz

Barrierefreiheit

• Text-to-Speech
• E-Mail des Verlags für Barrierefreiheitsfragen: [e-mail]
• Navigation über vor-/zurück-Elemente ohne Inhaltsverzeichnis
• Seitennummerierung folgt dem gedruckten Werk
• Mathematische Inhalte in MathML für assistive Technologien
• Text und Medien in logischer Lesereihenfolge angeordnet
• Navigierbarer Index mit direktem Zugriff auf Indexbegriffe
• Navigierbares Inhaltsverzeichnis für direkten Zugriff auf Text und Medien

Autor

Dr. Liu Peng is senior director and chief architect of business products at Qihoo 360. He is

also responsible for product and engineering for monetization of 360. After receiving his

PhD from Tsinghua University in 2005, he joined Microsoft Research Asia and studied

cutting-edge artificial intelligence technologies. In 2009, he participated in the founding of

Yahoo! Labs Beijing as a senior scientist. He was also chief scientist of MediaV. Dr. Liu

Peng is devoted to products and technologies related to big data and computational

advertising. His public online course "computational advertising" has attracted more than

30,000 students on Netease.com, and has been adopted as a basic training material in

many related companies. Moreover, this course has been selected by Peking University,

Tsinghua University and Beihang University for their graduates.

Wang Chao received his master's degree from Peking University, and then worked at

Weibo and Autohome's advertising department for some years. He is now a tech leader in

the query recommendation group at Baidu's portal search department. His work focuses on

machine learning algorithms in computational advertising, and he has won 7th place among

718 participants in "predict click-through rates on display ads" organized by Kaggle and

Criteo. He is also interested in contributing code for open source machine learning tools

such as xgboost.

Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 442
• Erscheinungstermin: 12. Mai 2020
• Englisch
• ISBN-13: 9780429557729
• Artikelnr.: 59436737