Optimizing International Talent Database Management Using Artificial Intelligence Algorithms

The international talent database plays a crucial role in modern globalized society, but its management faces many challenges, including issues such as large data volume, data quality, data security, and query efficiency. This article provides a detailed introduction to the AI (Artificial Intelligence) technology used, including machine learning, data mining, and automated query optimization. These technologies are applied to solve various problems in database management, such as data cleaning, anomaly detection, automated security, and performance optimization. Through the application of machine learning algorithms, we can automatically identify and correct data quality issues, improving the accuracy and completeness of data. In the experimental and results section, we described the design of the experiment and the analysis of the results. We validated the effectiveness of the proposed method through practical cases and simulated datasets. The experimental results show that AI algorithms can significantly improve the efficiency and effectiveness of international talent database management, reduce data errors, improve data security, and accelerate query speed.