Natural Language Query System with Interactive Ambiguity Resolution
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The increasing complexity and cost of managing and storing large volumes of data across various data storage systems pose challenges for organizations, as different data storage technologies offer varying performance benefits, leading to data dispersion across multiple locations and types of storage systems, making it difficult for users to interact with and analyze the data effectively.
Innovation Solution
Implementing a natural language query processing system that allows users to submit queries without knowing the underlying data storage system interfaces, using interactive assistance features like query assistance, auto-completion, and ambiguity handling to improve query performance and accuracy, and generating intermediate representations to execute queries across multiple data sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If data is stored across multiple different data storage systems to optimize performance and analysis benefits, then data storage performance is improved, but device complexity increases
Solution Approach 1:
The patent divides data storage across multiple specialized storage systems (object stores, database systems, data streams) where each handles specific types of data. This segmentation allows each storage system to be optimized for its specific function while the virtual data warehouse provides a unified interface, resolving the contradiction between performance optimization and system complexity.
Solution Approach 2:
The virtual data warehouse acts as an intermediary layer between users and the multiple underlying storage systems. It provides a unified interface that abstracts the complexity of multiple storage technologies, allowing users to query data without needing to understand the underlying distributed storage architecture, thus maintaining simplicity while enabling performance optimization.
2Adaptability or versatility
If data is distributed across multiple storage locations and types, then data analysis capability is improved, but ease of operation deteriorates
Solution Approach 1:
The virtual data warehouse provides a universal interface that works with multiple different storage systems and data types through a single standardized query mechanism. Users can analyze diverse data (objects, relational data, streams) using the same natural language or SQL interface, eliminating the need to learn different interaction methods for each storage type while maintaining access to all data types.
Solution Approach 2:
The virtual data warehouse serves as a mediator that translates user queries into appropriate operations on the underlying diverse storage systems. It handles the complexity of data distribution and retrieval automatically, allowing users to operate with simple, unified commands while the system manages the complexity of accessing data across multiple locations and formats.
3Manufacturing precision
If specialized data storage technologies are used for different data types, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The system segments data storage by type, using specialized storage technologies (object stores for unstructured data, relational databases for structured data, data streams for real-time data) where each is optimized for its specific data type. This segmentation enables high precision for each data type while the virtual data warehouse abstracts the complexity of managing multiple specialized systems.
Data Source
AI summary
Interactive assistances for executing natural language queries to data sets may be performed. A natural language query may be received. Candidate entity linkages may be determined between an entity recognized in the natural language query and columns in data sets. The candidate linkages may be ranked according to confidence scores which may be evaluated to detect ambiguity for an entity linkage. Candidate entity linkages may be provided to a user via an interface to select an entity linkage to use as part of completing the natural language query.