Intermediate Representation for Database-Agnostic Cypher Query Generation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional voice-based assistants face challenges in providing accurate answers due to random voice interactions and the need for extensive training to handle various database types and query formats, making it difficult to generate effective queries for knowledge bases.
Innovation Solution
A system and method that transforms natural language questions into an intermediate representation, which is then converted into a 'cypher query' to query a knowledge base, allowing for deterministic information retrieval irrespective of the database type, without requiring extensive training.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If direct query generation from natural language is used for various database types, then query accuracy may improve, but extensive training is required for each database type increasing system complexity
Solution Approach 1:
The patent introduces an intermediate representation layer between natural language input and database-specific queries. This intermediate representation serves as a mediator that captures the semantic meaning of the question in a database-agnostic format, allowing the system to generate accurate queries for different database types without requiring extensive training for each specific database schema.
2Ease of operation
If voice interaction is used for querying, then user convenience is improved, but query generation becomes more random and less effective
Solution Approach 1:
The intermediate representation acts as a stabilizing intermediary that converts the inherently variable and random nature of voice interactions into a structured, deterministic format. This allows the system to maintain high user convenience while improving query generation reliability by filtering out the randomness through the intermediate representation layer.
Solution Approach 2:
The system performs preliminary processing of voice input by converting it to an intermediate representation before generating the actual database query. This preliminary action structures the unstructured voice data, making subsequent query generation more reliable and deterministic.
3Measurement precision
If database-specific training is performed for each query format, then query accuracy improves, but the time and resources required for training increase substantially
Solution Approach 1:
The intermediate representation serves as a universal interface that can work with multiple database types and query formats without requiring separate training for each. This multi-functional approach allows a single training process on the intermediate representation to benefit all downstream database queries, dramatically reducing training time and resources.
Data Source
AI summary
The disclosed subject matter relates to a system and method for providing an automated assistant that retrieves information from a knowledge base in response to a user's natural language question. A user's natural language question voice is transformed into an intermediate representation. From the intermediate representation, a cypher query is generated which may be used to query the database. The query results are provided in response to the user. The transformation into the intermediate representation is database independent while the cypher query is dependent upon the database queried.