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This invention relates to the field of artificial intelligence technology, specifically to a personalized, in-depth cultural tourism planning system and method based on a large-scale artificial intelligence model. It includes a multi-source data fusion unit for constructing a dynamic cultural tourism knowledge graph; the experience nodes of the dynamic cultural tourism knowledge graph include hidden experience nodes obtained through data mining; a user intent understanding unit generates multi-dimensional user profile vectors; an intelligent planning and optimization unit generates personalized spatiotemporal travel plans, personal baggage preparation suggestions, global optimization of resource allocation, and dynamic personalized guidelines based on the dynamic cultural tourism knowledge graph and multi-dimensional user profile vectors; and a closed-loop feedback and evolution unit collects feedback data to update user profiles and optimize planning decisions. This system achieves automated mining and real-time fusion of multi-source unstructured data, thereby generating personalized plans that not only conform to users' deep cultural interests but are also highly feasible under actual spatiotemporal and resource constraints.