Natural Language Query Translation for Automated Data Integration
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Solution Overview
Problem
In sophisticated computing environments, existing software applications are typically generic and require customization after installation, leading to time-consuming and expensive processes for data integration between disparate systems, especially across different countries, necessitating a solution for translating software queries into natural language for user-friendly selection and execution.
Innovation Solution
A system and method that translates previously executed software queries into natural language, allowing users to select and combine them for data integration processes without needing to learn specific query syntaxes, using a graphical user interface to generate code instructions for accessing and retrieving data sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If generic software applications are used for data integration, then device complexity is reduced, but ease of operation deteriorates due to required customization and query syntax learning
Solution Approach 1:
The patent introduces a natural language processing intermediary that translates user-friendly natural language queries into formal query syntax. This mediator layer allows users to operate the system without learning complex query languages, while the system maintains the ability to execute sophisticated data integration tasks. The intermediary converts simple user intent into structured queries that can be processed by the integration system.
Solution Approach 2:
The system automatically generates and executes queries based on natural language input without requiring user configuration or customization. The automated integration process interprets user intent directly and performs data retrieval and integration tasks autonomously, eliminating the need for users to manually configure the system or learn operational procedures.
2Productivity
If customized data integration processes are implemented, then productivity is improved, but loss of time increases due to customization requirements
Solution Approach 1:
The system pre-configures automated integration processes with built-in query capabilities that can directly interpret natural language. Rather than requiring customization at deployment, the system comes pre-prepared with the intelligence to understand and execute user intent, eliminating the time-consuming customization phase while maintaining high productivity capabilities.
Solution Approach 2:
The patent transforms the operational parameter from formal query syntax to natural language. This parameter change allows the system to maintain sophisticated data integration functionality while accepting simple, human-readable input. The transformation occurs automatically through natural language processing, enabling users to achieve high productivity without investing time in learning complex query languages or configuring integration parameters.
3Measurement precision
If formal query syntax is used, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The natural language processing component serves as an intermediary that preserves measurement precision by accurately translating user intent into formally structured queries. The intermediary maintains the semantic meaning and precision requirements of the original natural language input while converting it into the structured syntax needed for accurate data retrieval and integration execution.
Data Source
AI summary
A method of translating software queries into natural language may comprise receiving a user instruction to identify a data set through a database query defined by a received user-selected query object and user-selected query value in setting a portion of a currently modeled integration process, and to perform a user-selected action on the data set, and translating a suggested database query associated in memory with the user-selected query object to a natural language translation. The method may also comprise displaying the natural language translation of the suggested database query, receiving a user instruction to include the suggested database query in the currently modeled integration process, and automatically generating and transmitting to a remote location for later execution, code instructions for performing the user-selected action on data sets stored at the remote database meeting the selected, suggested database query.