Natural Language Interface for Data Visualization Template Matching
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Solution Overview
Problem
Existing data visualization systems require users to have extensive knowledge of data science and visualization tools, limiting accessibility for business users who want to analyze data using natural language inputs.
Innovation Solution
A natural language interface that generates dashboards with multiple graphics by parsing user inputs, identifying relevant data sources and fields, and matching inputs to predefined data analysis templates, thereby creating dynamic visualizations without requiring users to build dashboards from scratch.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional data visualization tools are used, then data analysis capability is achieved, but user accessibility is limited due to requiring extensive data science knowledge
Solution Approach 1:
A natural language processing intermediary layer is introduced between the user and the data visualization system. This intermediary translates natural language queries into structured data analysis operations, eliminating the need for users to learn complex data science concepts while maintaining full data analysis capability. The system acts as a mediator that converts casual language into precise data queries.
Solution Approach 2:
The patent replaces the mechanical interaction model (where users manually configure visualization parameters and data fields) with a linguistic interaction model (where users simply type natural language questions). This substitution eliminates the need for users to understand the underlying mechanical complexity of data visualization systems while achieving the same analytical results.
2Ease of operation
If natural language interface is implemented, then user accessibility is improved, but system complexity increases due to parsing and template matching requirements
Solution Approach 1:
The system performs preliminary action by pre-defining multiple data analysis templates with associated natural language triggers before runtime. During operation, the system only needs to match user input against these pre-configured templates rather than performing complex real-time analysis. This shifts complexity from runtime processing to setup phase, making the operational system simpler.
Solution Approach 2:
The patent transforms the interaction paradigm by changing the input parameter from structured technical commands to unstructured natural language. This parameter change enables users to interact using their native language skills while the system handles the complexity of translating these varied inputs into standardized data analysis operations through template matching.
3Loss of information
If multiple data visualizations are generated from single query, then information completeness is improved, but processing time increases
Solution Approach 1:
Multiple data analysis templates are pre-configured with their associated visualizations before runtime. When a user submits a query, the system rapidly matches the query against multiple pre-defined templates simultaneously, generating comprehensive dashboards from a single query without requiring sequential processing of each visualization type.
Data Source
AI summary
A computing device receives, in a graphical user interface, a first natural language input directed to a first data source. The device parses the first natural language input and identifies one or more keywords from the input. The device identifies, using the keywords, a plurality of triggers for generating a respective plurality of data visualizations for the first data source. The device determines that the keywords in the first natural language input match a first data field or a first data value in a predefined set of data fields or a predefined set data values constrained by one or more variable terms specified via user configuration input. The computing device identifies a first trigger that is associated with a first plurality of data visualizations. The device generates the first plurality of data visualizations and displays a first data dashboard that includes the first plurality of data visualizations.