Natural Language Query Parsing With Node Trees for Accurate Data Filtering
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Solution Overview
Problem
Existing systems require users to choose query indexes and set restrictions manually, limiting the ability to query and filter data using natural language sentences.
Innovation Solution
A query selection system that processes natural language sentences to construct a node tree representing index-condition combinations, generating data query commands, and filtering results automatically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually select query indexes and set restrictions, then query accuracy is improved, but operation complexity and time consumption increase
Solution Approach 1:
The system automatically analyzes the natural language query, identifies relevant indexes and restrictions, and generates the query statement without requiring manual user configuration. The system serves itself by autonomously completing tasks that would otherwise require user intervention, thereby simplifying operation while maintaining query accuracy through automated semantic understanding and index selection.
2Measurement precision
If users manually collocate restrictions based on indexes, then query precision is improved, but time consumption increases
Solution Approach 1:
The system pre-processes the natural language query by identifying potential indexes and restrictions before generating the final query statement. By performing preliminary analysis and structuring of query components in advance, the system reduces the time required for manual configuration while ensuring that appropriate restrictions are correctly applied to maintain query precision.
3Adaptability or versatility
If the system provides multiple query indexes for user selection, then query versatility is improved, but device complexity increases
Solution Approach 1:
The system introduces an intermediary natural language processing layer between the user and the database query mechanism. This intermediary automatically translates user-friendly natural language into structured queries, eliminating the need for users to directly interact with complex index selection interfaces while still leveraging multiple indexes for versatile querying capabilities.
Data Source
AI summary
A system and method for query selection are provided. The method may include acquiring a natural language sentence, pre-processing to obtain a standard node sequence, constructing a node tree based on the relationship between an index node and other nodes, generating a data query command based on the node tree, querying data using the data query command, and filtering the results. The standard node sequence may include at least an index node and a condition node. The node tree may be used to characterize the index-condition combination. The system may include an acquisition unit, a pre-processing unit, a node tree construction unit, a translation unit, and a querying and filtering unit.