Design and Implementation of Real-Time Bidding Advertising System Based on Big Data Platform

In traditional digital advertising, advertisers disseminate information by exposing their advertisements on fixed advertising spaces they purchase. They can only purchase high-traffic advertising spaces to make their advertisements visible to the target audience as much as possible. This unbiased advertising, unrelated to audience information, results in resource waste. To solve the above questions, this article focuses on audience analysis and computational advertising as the research direction. A precise advertising placement system for real-time bidding of target audiences is constructed based on a big data platform. Five modules, including advertisement management, real-time bidding, audience persona, anti-cheat, and data collection, are designed and implemented in this system. Compared to traditional advertising delivery systems, this system matches precisely between advertising audiences and advertisements through technologies. It supports advertisers in purchasing advertising spaces generated by the target audience and enables them to purchase advertising spaces in real-time through real-time bidding according to the number of purchases. This solves the problem of effectively targeting different audience groups and optimizing bidding under big data, maximizing the benefits of advertising resources.