Natural Language Query Parsing for Database Visualization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
High-dimensional databases are challenging to query using natural language due to ambiguity, as they require structured query languages like SQL, making it difficult for computers to interpret and visualize data effectively.
Innovation Solution
A data visualization system with a processor and memory that uses a core grammar library and natural language query application to parse and execute natural language queries, generating suggested queries based on statistical analysis and extended grammar libraries to resolve ambiguity and visualize database data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If natural language queries are used to query high-dimensional databases, then ease of operation is improved, but measurement precision deteriorates due to ambiguity in interpreting user intent
Solution Approach 1:
The patent introduces an intermediary natural language processing system that acts as a mediator between the user's natural language query and the database's structured query requirements. This intermediary translates ambiguous natural language into precise database queries using techniques like query rewriting, schema linking, and contextual analysis, thereby resolving the contradiction between ease of operation and measurement precision.
Solution Approach 2:
The system dynamically changes parameters such as query complexity, level of abstraction, and processing depth based on the ambiguity detected in the natural language query. When ambiguity is detected, the system adjusts by requesting clarification, providing suggestions, or breaking down the query into multiple steps, thus adapting the precision requirements to match the operational ease.
2Measurement precision
If structured query languages like SQL are used, then measurement precision is improved, but ease of operation deteriorates due to complexity in syntax and structure
Solution Approach 1:
The patent creates a simplified copy or abstraction layer of the structured query language that mirrors natural language syntax. Instead of requiring users to learn complex SQL syntax, the system provides a natural language interface that copies the essential querying functionality while eliminating syntactic complexity, thus improving ease of operation while maintaining precision through backend translation.
Solution Approach 2:
The system segments the complex query process into multiple manageable stages: natural language input, intent detection, query planning, translation to structured queries, and execution. This segmentation allows users to interact with only the simple natural language portion while the complex structured operations are handled automatically in subsequent segments.
3Ease of operation
If natural language processing is implemented to handle ambiguity, then ease of operation is improved, but device complexity increases due to additional processing layers
Solution Approach 1:
The patent implements a universal natural language processing framework that handles multiple functions (parsing, semantics, ambiguity resolution, query generation) within a single integrated system. This multi-functional approach reduces overall device complexity compared to having separate specialized components for each processing task, while still providing comprehensive handling of natural language ambiguity.
4Productivity
If statistical analysis is performed to generate suggested queries, then productivity is improved through predictive querying, but use of energy increases due to computational requirements
Solution Approach 1:
The system performs partial statistical analysis by generating suggested queries only for the most ambiguous or critical portions of the natural language query rather than analyzing the entire query comprehensively. This partial action approach maintains productivity benefits through predictive querying while reducing energy consumption by limiting the scope of statistical computations to only where necessary.
Data Source
AI summary
Systems and methods for natural language querying in accordance with embodiments of the invention are illustrated. One embodiment includes a data visualization system, including a processor, and a memory, the memory including a core grammar library, comprising a list of regular expression-system function pairs, and a natural language query (NLQ) application, where the NLQ application configures the processor to obtain a database from a user, obtain an NLQ directed at the database, parse the NLQ using the core grammar library to identify a system function and a set of one or more parameters, and perform the system function using the set of one or more parameters to visualize at least a portion of the database.