Computational Advertising: Market and Technologies for Internet Commercial Monetization

Online advertising is more than a space to place an ad: it is a marketplace shaped by data, products, pricing, and algorithms. Computational Advertising brings those pieces together, showing how commercial goals and technical systems influence one another across the advertising ecosystem.

Peng Liu and Chao Wang’s second edition moves from the market foundations of online advertising into its products, trading models, and underlying technologies. The result is a useful cross-disciplinary view for readers who want to understand not just how ad systems work, but why they are designed as they are.

From advertising markets to the systems behind them

The book first establishes the context and fundamental concepts of online advertising, then examines the products and ways advertising is bought and sold. Its coverage includes agreement-based advertising, search ads and auctions, programmatic trading, and newer forms such as feed and native advertising. Seeing these models side by side helps readers follow how different commercial arrangements create different technical demands.

Where business decisions meet algorithms

Later chapters turn to the machinery that supports advertising products: data processing and exchange, audience targeting, auction-based methods, and click-through-rate prediction. The emphasis on business challenges alongside technical approaches gives product, operations, and engineering readers a shared framework for thinking about ad systems.

A broad view of computational advertising

Rather than treating advertising as a collection of isolated algorithms, Liu and Wang connect market structure, product design, data use, and system implementation. That perspective can help readers place individual techniques—such as targeting or prediction—in the wider process of matching advertising demand with available opportunities.

Who may find it useful

This book is aimed at readers engaging with online advertising from several angles: advertising and marketing professionals, product and operations teams, engineers, and students or researchers interested in computational advertising, machine learning, and internet monetization. Its progression from foundations and market models toward technical challenges offers a way into a field that can otherwise feel divided between business terminology and engineering detail.

For a grounded introduction to the market logic and technical architecture of online advertising, Computational Advertising offers a connected map of the field—from how ad products are traded to the data and algorithms that help them operate.