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With the rapid development of the global online advertising industry, computational advertising was born. As an advertising model that combines technology and calculation with online advertising decision-making, it is based on a given advertising request, takes into account the advertising context and user characteristics, selects the best match from the potential advertising library through calculation, and then runs deliver ads to target audiences. This article aims to start from the technical level of big data, accurately place online advertisements, and evaluate the effects of advertisements. The sample collection method and statistical analysis method are used to collect samples and set up a data transmission system based on BD-MQ. The experimental results of the research show that there is almost no profit in the study of advertising time between 4 and 8 o’clock, and the users who watched at 16 o’clock reached 34.7%, 18–20 o’clock reached 68.7%, 20–22 o’clock reached 80.1% of the peak, and 22–24 o’clock returned to 40.2%. Compared with the data transmission system based on ActiveMQ, the data transmission system based on BD_MQ designed in the thesis has a speed advantage of about 5%–10%, and the transmission rate changes for a single data with different sizes are more stable. The larger the total amount of data transmitted, the higher the average rate; the larger the single data packet, the higher the average rate. When the size of a single data packet is around 100 kB, the transmission rate reaches the maximum. The research on the precise placement and effect evaluation of online advertising has been completed well.

Accurate Delivery of Online Advertising and the Evaluation of Advertising Effect Based on Big Data Technology