CRC Press Computational Advertising: Market and Technologies for Internet Commercial Monetization

Product Description 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 advertising products.   Features ·         Introduces computational advertising and Internet monetization ·         Covers data processing, utilization, and trading ·         Uses business logic as the driving force to explain online advertising products and technology advancement ·         Explores the products and the technologies of computational advertising, to provide insights on the realization of personalization systems, constrained optimization, data monetization and trading, and other practical industry problems ·         Includes case studies and code snippets About the Author 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.