DOI: 10.38007/978-1-80053-610-4

To address the above challenges, artificial intelligence technology, especially the intelligent algorithm system centered on machine learning, deep neural networks, reinforcement learning and natural language processing, is rapidly penetrating into all levels of database systems with its forward-looking technological advantages and demonstrating unprecedented innovative potential and practical value in the field of data query optimization. Through the mining and learning of multi-dimensional information such as query history, data characteristics, and the usage of system resources, AI can not only dynamically adjust the query execution plan and intelligent recommendation index strategy, but also achieve the prediction of query paths, the optimization of caching mechanisms, and the automatic recognition of query intentions, thereby effectively improving query efficiency and reducing resource consumption. And enhance the adaptive ability and intelligent decision-making level of the database system in complex scenarios.

This book strives to balance theoretical depth and practical breadth in its content arrangement. It not only provides systematic theoretical support and research inspiration for academic researchers, but also offers practical guidance and solution ideas for database system engineers, artificial intelligence developers, and technical managers in related industries. Meanwhile, this book is also aimed at senior undergraduate and graduate students, dedicated to helping them master the key knowledge points of artificial intelligence in data query optimization, broaden their research horizons, enhance their comprehensive abilities, and lay a solid foundation for in-depth exploration in the field of intelligent databases and data management in the future.

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