Natural Language Interface for Cascading Data Visualization Edits
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Solution Overview
Problem
Current data visualization tools require users to learn complex interfaces, making it difficult for users to efficiently generate and update visualizations, especially for large or complex data sets, and can lead to errors if related phrases in natural language inputs are not updated correctly.
Innovation Solution
Implementing a method that automatically updates related phrases in natural language inputs used to generate data visualizations, allowing users to modify one phrase while automatically updating dependent phrases, reducing the cognitive burden and preventing errors by analyzing user inputs and updating the graphical user interface accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users manually update all related phrases in natural language expressions when modifying data visualizations, then accuracy and reliability are improved, but ease of operation and time consumption deteriorate
Solution Approach 1:
The system automatically detects dependencies between phrases and updates them without user intervention. When a user modifies one phrase, the system self-services by identifying and updating all dependent phrases, eliminating the need for manual updates while maintaining accuracy.
Solution Approach 2:
The system provides feedback by analyzing the natural language expression structure, identifying dependency relationships between phrases, and automatically propagating updates. This feedback mechanism ensures that all related phrases are consistently updated when one phrase changes.
2Reliability
If users manually update all related phrases in natural language expressions when modifying data visualizations, then reliability is improved, but time consumption worsens
Solution Approach 1:
The system performs preliminary analysis of the natural language expression structure to identify dependency relationships between phrases before user input. This preliminary action enables automatic update propagation, eliminating the time-consuming manual update process while ensuring reliability.
Solution Approach 2:
The system automatically detects and updates dependent phrases without requiring user time investment. The self-service mechanism analyzes the expression structure, identifies dependencies, and propagates updates autonomously, significantly reducing time consumption while maintaining accuracy.
3Adaptability or versatility
If complex user interfaces are used for data visualization tools, then functionality and versatility are improved, but ease of operation deteriorates
Solution Approach 1:
The system introduces an intermediary natural language interface between the user and the complex data visualization functionality. Users interact through simple natural language expressions, and the intermediary system handles the complexity of parsing, analyzing dependencies, and generating visualizations, thereby maintaining versatility while improving ease of operation.
Solution Approach 2:
The system provides self-service by automatically analyzing the natural language input, identifying phrase dependencies, and updating related phrases without user intervention. This self-service capability handles the operational complexity internally, allowing users to access sophisticated functionality through simple natural language commands.
Data Source
AI summary
A method is performed at a computing device having a display, one or more processors, and memory. The device displays a graphical user interface on the display. A user provides a natural language input, which specifies a filter, including a first data field, a relation, and a first comparison value. The user then replaces the first data field in the filter with a second data field. In response to replacing the first data field, the device automatically replaces the first comparison value with a second comparison value. The second comparison value corresponds to the data type of the second data field. In some instances, the device also updates the relation based on the data type of the second data field. The device then displays an updated data visualization according to the updated filter.