Multi-modal dynamic fusion chart visualization method, system, device and medium
By employing a multimodal dynamic fusion chart visualization method, and combining knowledge graphs and WebGL engines with machine learning, the problem of modal fragmentation and interaction lag in multi-source heterogeneous data is solved, achieving efficient and intuitive data analysis and intelligent interaction, thereby improving user experience and system performance.
Patent Information
- Application Number
- CN202610795361.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-06-04
- Publication Date
- 2026-07-03
AI Technical Summary
Existing technologies suffer from modal fragmentation, delayed interaction, insufficient expressiveness, and performance bottlenecks when presenting multi-source heterogeneous data. This results in high cognitive load and low exploration efficiency for users when analyzing complex scenarios, making it difficult to intuitively understand the dynamic relationships and semantic information hidden in the data.
A multimodal dynamic fusion chart visualization method is adopted. Entities and their relationships are constructed through knowledge graphs, and data is dynamically expressed using WebGL particle rendering engine and physics engine. Intelligent interactive response is achieved by combining machine learning intent recognition model, generating unified semantic visualization units.
It achieves a unified visual representation of multimodal data, enhances the visual expressiveness of complex dynamics and relationships, reduces the cognitive and operational load on users, and ensures the consistency of cross-device experience and smooth stability under large-scale data.
Smart Images

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