Question Answering Robot Generation via Semantic Expansion
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Solution Overview
Problem
Developing field-specific question answering robots is labor-intensive due to the need for extensive configuration of question-answer pairs, resulting in high labor costs.
Innovation Solution
A method that involves obtaining field information from users, retrieving a field-specific robot from a library, providing a template list, receiving user-filled templates, expanding questions using a semantic database to form question-answer pairs, and generating a question answering robot based on these pairs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If developers manually configure many question-answer pairs to build a field-specific question answering robot, then the robot can satisfy needs of different customers with comprehensive functions, but it will take high labor cost and time
Solution Approach 1:
The system pre-configures question-answer pair templates with placeholder variables before actual use. Developers don't need to manually create complete question-answer pairs from scratch; instead, they can reuse pre-defined templates that already have the correct structure and logic, significantly reducing the time and labor required to build field-specific robots while maintaining comprehensive functionality
Solution Approach 2:
The system enables copying and reusing of question-answer pair templates across different fields and customers. Once a template is created for one field, it can be copied and adapted for other fields by simply replacing the placeholder variables with field-specific values, eliminating the need to manually configure similar question-answer pairs repeatedly for different customers
2Adaptability or versatility
If developers manually configure question-answer pairs for different fields, then the robot can be customized for specific fields, but the process becomes complex and time-consuming
Solution Approach 1:
The system extracts the common structural elements and logic from question-answer pairs into reusable templates. By separating the template structure (which remains constant) from the field-specific content (which varies), the system simplifies the configuration process. Developers only need to provide field-specific information while the system handles the complex template matching and variable replacement automatically
Solution Approach 2:
The question-answer pair templates are designed to be universal and field-agnostic. A single template can serve multiple fields by using placeholder variables that can be replaced with different field-specific values. This universality allows the same template to generate customized question-answer pairs for different fields without requiring separate configurations for each field
Data Source
AI summary
The present disclosure discloses a method for generating a question answering robot, relates to the field of robotics. The specific implementation includes: obtaining field information input by a user, obtaining a field-specific robot from a robot library based on the field information; obtaining a template list corresponding to the field-specific robot, providing the template list to the user, the template list including a plurality of templates; receiving the plurality of templates filled in by the user, the templates filled in by the user including at least one question and an answer corresponding to the at least one question; expanding the at least one question filled in by the user based on a question semantic database to form a combination of questions corresponding to the answer, the answer and the combination of questions forming a question-answer pair; and generating a question answering robot based on the question-answer pair.