Intelligence Augmentation System for Customized Data Visualization
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Solution Overview
Problem
Current systems in work environments lack efficient methods to provide users with relevant and accurate visualizations of complex data, leading to unnecessary resource utilization and inaccuracies in response generation, as they often display irrelevant information in response to user requests.
Innovation Solution
A customized visualization based intelligence augmentation system that uses an iterative request refiner, request classifier, and visualization analyzer to refine user requests, classify them into awareness, alert, or advice categories, and generate insight outputs mapped to specific visualizations with embellishments, reducing irrelevant data display and enhancing accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current systems display all available data in response to user requests, then users receive comprehensive information, but computing resources are wasted and irrelevant information is displayed
Solution Approach 1:
The system extracts only the relevant portion of data from the complete dataset based on user intent classification. The visualization analyzer generates customized visualizations that display only the specific information needed to answer the user's question, rather than displaying all available data. This extraction process eliminates irrelevant information display while maintaining accuracy.
Solution Approach 2:
The system applies different levels of data processing and visualization customization to different parts of the information space. Based on the classified user intent (awareness, alert, or advice), the system tailors the visualization content, detail level, and presentation format to match the specific information needs, rather than applying a uniform display approach to all data.
2Productivity
If current systems generate visualizations for all user requests, then users receive responses to all inquiries, but inaccuracies occur due to irrelevant information inclusion
Solution Approach 1:
The system performs preliminary classification of user requests into intent categories (awareness, alert, advice) before generating visualizations. This preliminary action allows the system to pre-determine the appropriate level of detail, data sources, and visualization type needed, thereby improving both the efficiency of response generation and the accuracy of the information provided.
Solution Approach 2:
The system uses feedback from the user request analysis to continuously refine the visualization generation process. The classification results and user interactions inform subsequent visualization customization, ensuring that the displayed information accurately matches user needs while improving response generation efficiency through learned patterns.
3Measurement precision
If the system refines user requests through iterative processes, then response accuracy improves, but processing time increases
Solution Approach 1:
The system applies iterative refinement only to the extent necessary for accurate intent classification. Rather than performing exhaustive analysis on all requests, the system applies refinement steps selectively based on request complexity and ambiguity, achieving sufficient accuracy without unnecessary processing time expenditure.
Data Source
AI summary
According to an example, customized visualization based intelligence augmentation may include accessing, based on a user request, a domain model, and mapping the user request to the domain model. Based on the mapping, a guided query that includes a relevant refinement question may be generated. A response may be received to the refinement question. Based on the received response, a refined user request may be generated, and classified into an intelligence augmentation category. Based on the classification, an intelligence augmentation analyzer may be accessed to analyze the refined user request to generate an insight output that is classified to a visualization. Based on the classification of the insight output to the visualization, responsive to the user request, a display of the visualization may be generated.