Inquiry Information Processing Using Knowledge Graph Question Generation
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Solution Overview
Problem
Current inquiry information processing methods have low efficiency due to the need for manual procedures when target answer data does not match user input, leading to inefficient diagnosis and treatment processes.
Innovation Solution
An inquiry information processing method that determines user disease features, performs disease prediction, and generates target questions dynamically using a knowledge graph to improve the accuracy and efficiency of inquiries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If pre-configured question and answer pairs are used for inquiry processing, then the system structure is simple, but the inquiry efficiency is low when target answer data does not match user input
Solution Approach 1:
The system automatically generates target questions and retrieves answer data without manual intervention. The processing module autonomously determines whether to trigger manual inquiry procedures, enabling the system to serve itself and improving inquiry efficiency while maintaining reasonable complexity levels
Solution Approach 2:
The system pre-configures question and answer pairs in advance, preparing the knowledge base before actual inquiry processing. This preliminary preparation enables faster response when matches are found, improving efficiency without requiring complex real-time processing
2Reliability
If manual inquiry procedures are triggered when target answer data is not found, then complete diagnosis can be achieved, but the inquiry efficiency decreases
Solution Approach 1:
The processing module receives feedback from the matching process and automatically determines whether to trigger manual inquiry procedures. This feedback mechanism ensures complete diagnosis is achieved only when necessary, maintaining high inquiry efficiency by avoiding unnecessary manual interventions while preserving diagnosis accuracy
Data Source
AI summary
Embodiments of this application provide an inquiry information processing method performed at a computing device. The method specifically includes: determining user disease features according to at least one user input; performing disease prediction on the user disease features to obtain corresponding candidate diseases; acquiring question entities from a knowledge graph according to disease feature entities corresponding to the candidate diseases, the question entities being used for representing questions related to the disease feature entities; and generating target questions according to the question entities, the target questions being used for performing an inquiry on a user. By means of the embodiments of this application, the accuracy of target questions for an inquiry can be improved, thereby improving the inquiry efficiency.