Query Statement Generation Using Context Semantic Vectors
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Solution Overview
Problem
Current methods for generating query statements in automatic machine question answering systems lack accuracy and reliability due to insufficient consideration of context semantic information.
Innovation Solution
A method that determines a first vector representation based on known nodes in a syntax tree, uses a preset copy reference matrix to determine a target generation strategy, and generates the query statement by performing this strategy, incorporating context semantic information from adjacent query statements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If query statement generation does not consider context semantic information, then the generation process is simple and fast, but the accuracy and reliability of generated queries are insufficient
Solution Approach 1:
The patent performs preliminary actions by extracting context semantic information from adjacent query statements before generating the target query statement. The system retrieves and processes contextual information from the knowledge base in advance, so that when generating the query statement, the context is already prepared and can be directly integrated, thereby improving accuracy without significantly increasing the overall generation time
Solution Approach 2:
The patent introduces context semantic information as an intermediary element between the query generation process and the knowledge base. This intermediary allows the system to bridge the gap between simple generation processes and accurate query statements by using contextual information as a mediator that enriches the generation process with relevant semantic meaning
2Reliability
If query statement generation does not consider context semantic information, then the generation process is fast, but the reliability of generated queries is insufficient
Solution Approach 1:
The system performs preliminary extraction and processing of context semantic information from adjacent query statements before the main generation process. By preparing contextual information in advance from the knowledge base, the system can quickly integrate it during generation without significant time delay, thereby improving reliability while maintaining fast generation speed
Solution Approach 2:
The patent incorporates feedback mechanisms where the generated query statement is validated against the context semantic information and knowledge base. This feedback loop ensures reliability by checking whether the generated query accurately reflects the intended meaning and contextual information, allowing for corrections if necessary without requiring complete regeneration
Data Source
AI summary
The disclosure provides a method for generating a query statement. The method includes: determining a first vector representation based on known nodes in a first syntax tree corresponding to a query statement to be generated; determining a target generation strategy corresponding to a target node to be generated based on the first vector representation and a preset copy reference matrix; generating the target node based on the first vector representation or a second vector representation by performing the target generation strategy, in which the second vector representation is a vector representation corresponding to an adjacent query statement prior to the query statement to be generated; and generating the query statement based on the known nodes and a terminator in response to the target node being the terminator.