Intelligent guide method and system based on computer vision and knowledge graph

CN121599601APending Publication Date: 2026-03-03GUANGZHOU POWER SUPPLY BUREAU GUANGDONG POWER GRID CO LTD
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Patent Information

Application Number
CN202511474890.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-10-15
Publication Date
2026-03-03

AI Technical Summary

Technical Problem

The electricity marketing business faces challenges such as low review efficiency, poor user experience, data mismatch, difficulty in knowledge accumulation, and shortcomings in intelligent systems, making it unable to adapt to the needs of digital transformation.

Method used

An intelligent guidance method based on computer vision and knowledge graphs is adopted. Through document ambiguity classification processing, multimodal recognition, cross-source data verification, knowledge graph-driven reasoning and dynamic rule adaptation, combined with AI preliminary review and expert review, the business process is automated and intelligent.

Benefits of technology

Significantly reduce business review time, decrease labor costs, lower form-filling error rates, unify cross-departmental data standards, form reusable digital knowledge assets, and improve user satisfaction and service response speed.

✦ Generated by Eureka AI based on patent content.

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Abstract

The invention discloses an intelligent guide method and system based on computer vision and a knowledge graph, and relates to the technical field of artificial intelligence, and the method comprises the following steps: business initiation and image preprocessing, multi-modal identification and cross-source data verification, knowledge graph driven reasoning, dynamic rule adaptation, and man-machine cooperation recheck and knowledge closed loop. According to the invention, through AI preliminary review + expert accurate review, cross-department data verification and intelligent filling, the review efficiency and the control quality are improved, and the user experience is optimized; technical shortages are broken through, dynamic updating of industry specifications is realized, visual requirements of a power scene are adapted, and a knowledge graph is also constructed to precipitate reuse knowledge; and meanwhile, cost is saved, power grid safety is guaranteed, high-quality service scale is promoted, and power grid digital transformation is supported.
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