Method and device for evaluating maintenance service, computer device and storage medium
By using a pre-set voice inquiry graph and intent recognition model, the problem of poor accuracy in manual evaluation in the repair industry is solved, and efficient, accurate matching and standardized processing of user evaluations and repair records are achieved.
CN121683807BActive Publication Date: 2026-08-18BEIJING SHANSHAN INTERNET FUTURE TECHNOLOGY CO LTD
2 Cites 0 Cited by
Patent Information
- Application Number
- CN202511956648.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-23
- Publication Date
- 2026-08-18
- Estimated Expiration
- 2045-12-23
AI Technical Summary
Technical Problem
In the traditional repair industry, repair technicians rely on manual telephone follow-ups to evaluate customer satisfaction, resulting in poor data accuracy and consistency.
Method used
Using a pre-defined voice inquiry graph and intent recognition model, the system accurately matches user reviews with maintenance records and generates standardized evaluation results through voice conversion, keyword extraction, attention mechanism fusion, and sentiment analysis.
Benefits of technology
It improves the accuracy and consistency of maintenance service evaluations, reduces misunderstandings caused by semantic ambiguity, and achieves efficient integration of user evaluations and maintenance records.
✦ Generated by Eureka AI based on patent content.
Abstract
The application relates to a maintenance service evaluation method and device, computer equipment and a storage medium. The maintenance service evaluation method comprises the following steps: obtaining a preset voice inquiry graph; obtaining an evaluation voice of a user, converting the evaluation voice into evaluation text, and inputting the evaluation text into an intention recognition model; obtaining a maintenance record corresponding to the evaluation voice, extracting a keyword in the evaluation text through the intention recognition model, fusing the keyword and a maintenance feature vector in the maintenance record based on an attention mechanism to obtain a fused feature vector; the intention recognition model performs similarity matching on the fused feature vector in a preset question node and an intention node at each level, and if a most matched intention node is obtained, the most matched intention node is taken as a most matched feature vector; and the most matched feature vector and a follow-up result node corresponding to the most matched intention node are fused to obtain an evaluation result. The evaluation method provided by the application provides an evaluation standard and solves the problems of accuracy and consistency.
Need to check novelty before this filing date? Find Prior Art