一种基于人工智能的广告定向投放方法及系统
By constructing an association graph of advertising targeting issues and multi-factor evaluation, combined with real-time user behavior data, the problem of insufficient real-time response and lagging strategy adjustment in existing advertising targeting methods is solved. This enables dynamic quantitative evaluation and optimization of advertising performance, improving the accuracy of targeting and return on investment.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Filing Date
- 2026-06-17
- Publication Date
- 2026-07-17
AI Technical Summary
Existing advertising targeting methods struggle to achieve continuous, real-time monitoring and dynamic response to user behavior data, resulting in insufficient targeting accuracy, delayed strategy adjustments, an inability to effectively capture immediate opportunities or risks arising from rapid changes in user behavior, and a lack of systematic and intelligent multi-dimensional factor evaluation mechanisms.
By using artificial intelligence-based methods, combining historical ad delivery logs and real-time user behavior data, an ad targeting problem association graph is constructed. The PAGERANK algorithm is used to evaluate the potential effect value, and cosine similarity is used to calculate the real-time presence degree to evaluate the effect improvement index. Finally, the optimal ad strategy is evaluated through a comprehensive assessment of multiple factors.
It enables dynamic and quantitative evaluation of advertising performance, improves the accuracy and real-time nature of targeting, enhances the scientific and targeted nature of strategic decisions, increases the agility and effectiveness of campaign optimization, and significantly improves advertising performance and return on investment.
Smart Images
Figure CN122415170A_ABST