Natural Language Query System for Enterprise Data
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Solution Overview
Problem
Conventional enterprise software systems require users to possess familiarity with defined logical objects and query syntax, leading to inefficiencies in formulating and refining queries, especially as the complexity of desired results increases, and they struggle to support queries that do not conform to defined syntax.
Innovation Solution
A system architecture that parses an input text string to determine a limited set of candidate queries, using a dictionary and grammar to match entities and phrases, and scores these queries to present the top-scoring ones to the user, allowing for natural language queries and reducing the complexity of query formulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional query syntax and logical objects are used, then query precision and data accuracy are improved, but user operation complexity and time consumption increase significantly
Solution Approach 1:
The patent introduces a natural language processing intermediary layer between the user and the database query system. This intermediary translates user-friendly natural language queries into formal database queries, eliminating the need for users to learn complex query syntax while maintaining query precision through structured translation rules and validation mechanisms.
Solution Approach 2:
The patent replaces the mechanical syntax-based query formulation system with a semantic understanding system. Instead of requiring users to follow rigid syntax rules and join logical objects mechanically, the system uses natural language processing to understand query intent and generate appropriate queries, significantly reducing operational complexity.
2Reliability
If strict query syntax enforcement is implemented, then query reliability is improved, but system adaptability and user flexibility deteriorate
Solution Approach 1:
The patent implements a dynamic query processing system that adapts to different user input styles and complexities. The system dynamically adjusts its processing approach based on the natural language query characteristics, applying appropriate parsing strategies and validation rules to maintain reliability while accommodating diverse query formulations and evolving user needs.
Solution Approach 2:
The patent changes the fundamental parameter of query input from structured syntax to unstructured natural language. This parameter change enables the system to accept queries in various forms and complexities while maintaining reliability through semantic analysis and intent recognition, rather than relying on rigid syntax enforcement.
3Adaptability or versatility
If comprehensive query options are provided, then query functionality is improved, but information overload and user decision difficulty increase
Solution Approach 1:
The patent extracts and prioritizes the most relevant query options and results based on the natural language input analysis. Instead of presenting all possible query formulations and options, the system identifies and presents only the most relevant ones, reducing information overload while maintaining comprehensive functionality for the specific user intent.
4Ease of operation
If natural language processing is implemented, then ease of operation is improved, but system complexity and processing time increase
Solution Approach 1:
The patent segments the natural language processing system into distinct functional modules: intent recognition, entity extraction, query construction, and validation. This segmentation allows each module to handle specific aspects of query processing independently, managing system complexity through modular design while maintaining ease of operation through specialized processing for each segment.
Data Source
AI summary
A system includes reception of an input string of words, determination, for each subset of consecutive one or more words in the input string, of one or more phrase types based on the subset, on a dictionary describing a plurality of entities, each of the plurality of entities associated with an entity type, and on a grammar describing a plurality of phrase types, each of the plurality of phrase types associated with one or more conditions, and determination of a plurality of candidate queries based on the determined phrase types.