Dashboard Heatmap Story Generation
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Solution Overview
Problem
Conventional business analytics applications fail to capture user interactions and interests, making it difficult to infer user preferences and generate personalized stories and explorations.
Innovation Solution
A computer-implemented method that tracks user movements on dashboards, generates heatmaps with hotspots, creates bounding boxes, maps these to visualizations, and generates tree diagrams to automatically produce personalized stories and explorations based on user interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional business analytics applications are used to visualize and analyze data, then data visualization and analysis capabilities are provided, but user interactions and interests are not captured
Solution Approach 1:
The system preemptively captures user interaction data (eye movements, clicks, hovers) as users view dashboards, storing this information for later analysis. This preliminary capture of interaction patterns enables subsequent generation of personalized stories and explorations without requiring additional user input during the analysis phase.
Solution Approach 2:
The patent introduces an intermediary processing layer that receives raw user interaction data, processes it through heatmap generation and hotspot detection algorithms, and transforms it into structured insights about user interests. This intermediary layer bridges the gap between raw interaction data and personalized content generation.
2Adaptability or versatility
If user interactions are tracked and analyzed to generate personalized content, then personalized stories and explorations are created, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary processing of user interaction data by generating heatmaps and identifying hotspots during or immediately after dashboard viewing sessions. This advance processing creates ready-to-use structured data about user interests, enabling rapid generation of personalized stories and explorations when needed without requiring extensive real-time computation.
3Measurement precision
If heatmaps and hotspots are generated from user movements to identify interested visualizations, then user interests are accurately detected, but computational processing complexity increases
Solution Approach 1:
The system extracts only the most relevant features from raw user interaction data by generating heatmaps that concentrate attention on hotspot regions. This extraction process filters out unnecessary data details and focuses computational resources on identifying and analyzing only the visualizations that genuinely captured user interest, as represented by hotspot locations.
Data Source
AI summary
A computer-implemented method includes tracking, by a computer device, movements of a user viewing a dashboard containing visualizations. The method also includes generating, by the computer device, heatmaps having hotspots onto the dashboards in view of the tracked movements of the user. Additionally, the method includes generating, by the computer device, bounding boxes around the hotspots. Further, the method includes mapping, by the computer device, the bounding boxes to the visualizations. The method also includes creating, by the computing device, a tree diagram listing the hotspots which correspond to the bounding boxes. Additionally, the method includes generating automatically, by the computing device, a story or exploration from the tree diagram.