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Peng Liu

Computational Advertising

Market and Technologies for Internet Commercial Monetization

Ebook (EPUB Format)

This book introduces computational advertising, and Internet monetization. It provides a macroscopic understanding of how consumer products in the Internet era push user experience and monetization to the limit. Part One of the book focuses on the basic problems and background knowledge of online advertising. Part Two targets the product, operations, and sales staff, as well as high-level decision makers of the Internet products. It explains the market structure, trading models, and the main products in computational advertising. Part Three targets systems, algorithms, and architects, and focuses on the key technical challenges of different a… Mehr

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Produktdetails


Weitere Autoren: Wang, Chao
  • ISBN: 978-0-429-55772-9
  • EAN: 9780429557729
  • Produktnummer: 34052626
  • Verlag: Taylor & Francis Ltd.
  • Sprache: Englisch
  • Erscheinungsjahr: 2020
  • Seitenangabe: 442 S.
  • Plattform: EPUB
  • Masse: 15'312 KB
  • Auflage: 2. Auflage
  • Abbildungen: 131 schwarz-weiße Abbildungen, 17 schwarz-weiße Tabellen

Über den Autor


Dr. Liu Peng is senior director and chief architect of business products at Qihoo 360. He isalso responsible for product and engineering for monetization of 360. After receiving hisPhD from Tsinghua University in 2005, he joined Microsoft Research Asia and studiedcutting-edge artificial intelligence technologies. In 2009, he participated in the founding ofYahoo! Labs Beijing as a senior scientist. He was also chief scientist of MediaV. Dr. LiuPeng is devoted to products and technologies related to big data and computationaladvertising. His public online course computational advertising has attracted more than30,000 students on Netease.com, and has been adopted as a basic training material inmany 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 atWeibo and Autohome's advertising department for some years. He is now a tech leader inthe query recommendation group at Baidu's portal search department. His work focuses onmachine learning algorithms in computational advertising, and he has won 7th place among718 participants in predict click-through rates on display ads organized by Kaggle andCriteo. He is also interested in contributing code for open source machine learning toolssuch as xgboost.

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