Computational Advertising

Regular price €137.99
A01=Chao Wang
A01=Peng Liu
Ad Call
Ad Serving
advanced online advertising technologies
Advertiser Website
advertisiing
Advertising Effect
advertising monetization
Advertising Platform
auction based advertising
auction theory applications
audience segmentation techniques
Author_Chao Wang
Author_Peng Liu
Big Data
big data monetization
Category=KJE
Category=KJSA
Category=UN
Computational Advertising
data privacy compliance
Demand Node
digital marketing analytics
DNN Model
eq_bestseller
eq_business-finance-law
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Exponential Family Distribution
Google Play
information retrieval
Integral Wall
internet entrepreneurs
Inverted Index
KD Tree
machine learning optimisation
Mobile Advertising
Native Ad
Native Advertising
Online Advertising
personalization system
PR Curve
programmatic advertising systems
programmatic trading
Roc Curve
Search Ad
search ads
Search Advertising
Supply Node
User Id
User Tag
Visitor Data Set

Product details

  • ISBN 9780367206383
  • Weight: 957g
  • Dimensions: 178 x 254mm
  • Publication Date: 27 May 2020
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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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

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.