Actionable Answer Card for Natural Language Query Refinement
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Solution Overview
Problem
Current database management systems and data analytics applications lack the ability to efficiently query complex data using natural language, and once results are obtained, users cannot further manipulate or share them in a comprehensive manner, leading to inefficiencies and frustration.
Innovation Solution
Implementing a Natural Language Query (NLQ) system that allows users to ask questions in a conversational interface, process queries using predefined templates, and generate actionable answer cards that can be edited, shared, and further queried, enabling continuous workflow and real-time data manipulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users query complex data using traditional database management systems, then they can obtain query results, but the process is difficult and time consuming requiring users to start over with new queries if results do not fit needs
Solution Approach 1:
The patent implements dynamic query refinement by allowing users to interactively modify query parameters and naturally language questions after initial results are generated. The system continuously adapts query results based on user feedback without requiring complete query restarts, enabling iterative refinement of data exploration.
Solution Approach 2:
The system maintains continuous workflow by preserving query context and results across multiple interactions. Users can build upon previous queries through natural language follow-up questions, and the system continuously provides relevant results without interrupting the analytical workflow, eliminating the need to start over.
2Adaptability or versatility
If users obtain query results as snapshots, then they can view data at a specific time, but they cannot continue work with results in a comprehensive manner to focus answers while maintaining real-time data access
Solution Approach 1:
The patent creates answer cards that serve multiple functions: they display query results, allow interactive refinement through natural language questions, enable sharing with collaborators, and maintain real-time data connectivity. This multi-functional component eliminates the need for separate tools for different data manipulation tasks.
Solution Approach 2:
The answer card acts as an intermediary between the database system and the user, maintaining real-time data connections while providing a stable interface for interaction. It mediates between snapshot visualization and continuous data access, allowing users to work with results as if static while maintaining live data connectivity in the background.
3Ease of operation
If typical applications require users to start over with new queries when answer content does not fit needs, then query results can be obtained, but user workflow is halted creating inefficiencies and frustration
Solution Approach 1:
The system implements continuous feedback loops where user interactions with answer cards, natural language questions, and result refinements are immediately processed and reflected in updated results. This real-time feedback mechanism allows users to iteratively improve query outcomes without workflow interruptions.
Solution Approach 2:
The system performs preliminary data exploration and analysis before users need to request specific results. By pre-processing data and maintaining query context, the system is ready to immediately respond to user follow-up questions without requiring users to restart their analytical workflow.
Data Source
AI summary
System, method, and computer product embodiments are described for querying a database using natural language queries (NLQ) to produce actionable results in an answer card. The method allows a user to take further action with the answer card by editing the card contents, manipulating the way data is displayed, or querying the answer results for more details of the data. By the method, the user may continue exploration of the data, use the results to collaborate with others, or build a story from the data in a presentation format, such as a dashboard, while maintaining access to the real-time data of the database through the answer card. System and computer product embodiments implement the method.