A multi-stage scene linkage AI interactive narrative generation and management method

CN121412419BActive Publication Date: 2026-06-05YANCHENG XINLI NETWORK TECHNOLOGY CO LTD

Patent Information

Authority / Receiving Office: CN · China
Patent Type: Patents(China)
Current Assignee / Owner: YANCHENG XINLI NETWORK TECHNOLOGY CO LTD
Filing Date: 2025-10-28
Publication Date: 2026-06-05

AI Technical Summary

Technical Problem

Traditional large-scale model generation methods struggle to balance computational power consumption and content consistency when generating entertainment products, making it difficult for users to obtain the high-quality content they desire over a longer period.

Method used

We adopt a multi-level scene linkage AI interactive narrative generation and management method. By constructing a multi-level scene architecture with dynamic adaptability, we define the core narrative dimensions and hierarchical relationship logic of the scene. Combined with AI pre-trained element association model and intelligent trigger logic, we generate personalized scene exploration paths. Through multimedia collaborative output and management, we ensure the consistency of narrative content and adjust according to user feedback.

Benefits of technology

It achieves a balance between scene load and experience during user interaction, accurately matches scene environment and character interaction, reduces invalid interaction, enhances narrative coherence, generates personalized content that meets user needs, and improves user engagement and satisfaction.

✦ Generated by Eureka AI based on patent content.

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Abstract

The application discloses a kind of multi-level scene linkage's AI interactive narrative generation and management method, it is related to intelligent AI interaction field, including: based on AI narrative big model constructs with dynamic adaptation ability multi-level scene architecture, define the core narrative dimension of each level scene, and preset the hierarchical association logic and interactive permission boundary between scene;Establish the multi-level narrative element database of the AI pre-training element association model, store scene environment parameters, character interaction attributes and event trigger threshold in each level database classification, and configure the real-time dynamic supplement interface of database element;The application can balance user interaction experience and scene load stability through dynamic adaptation coefficient, avoid scene overload, improve running smoothness, and the multi-level narrative element database established can accurately match the storage scene environment, character interaction and event trigger related elements by element correlation degree, provide accurate data support for narrative.

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