Visual Identification Indicia for Concept Relationship Visualization
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Solution Overview
Problem
Existing computerized user interfaces struggle to effectively visualize complex relationships among diagnostic concepts in a manner that is both clear and accessible, particularly for users with visual impairments or assistive technology needs, and fail to optimize input component enablement in electronic group meetings.
Innovation Solution
A computer-implemented method and system that determine unique visual identification indicia for concepts using a combination of appearance style elements with sufficient contrast, enabling clear visualization of relationships among concepts and optimizing input component enablement by identifying quality metrics and focusing on relevant audio inputs in group meetings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If visual identification indicia use basic appearance styles without sufficient contrast, then the visualization is simpler to generate, but the distinguishability of relationships among concepts deteriorates
Solution Approach 1:
The patent applies local quality by assigning different appearance style elements (colors, line styles, thicknesses, endmarks) to different visual identification indicia based on their specific relationships. Each concept's visual indicators are locally optimized to reflect its unique relationships with other concepts, enabling precise distinction of complex diagnostic relationships while maintaining a systematic approach to visualization.
2Loss of information
If the system uses multiple visual attribute categories with sufficient contrast, then the clarity of concept relationships improves, but the complexity of selecting and managing appearance styles increases
Solution Approach 1:
The patent segments the visual identification system into distinct attribute categories (color, line style, thickness, endmarks). Each category is independently managed and can be selectively applied to visual identification indicia. This segmentation allows the system to maintain rich visual differentiation capability while simplifying the management complexity by organizing attributes into discrete, manageable categories that can be independently configured.
3Ease of operation
If the visualization system accommodates visual accessibility considerations, then the accessibility for users with visual impairments improves, but the constraints on appearance style selection increase
Solution Approach 1:
The patent implements parameter changes by providing multiple variants within each visual attribute category that are optimized for different accessibility requirements. For example, color attributes include options with varying luminance contrasts, line styles include variations in thickness and pattern, and endmarks include different shapes and sizes. This allows the system to adapt visual parameters to meet accessibility needs while preserving versatility through the availability of multiple configurable options within each category.
4Measurement precision
If the system iteratively determines unique visual identification indicia for each concept, then the precision of relationship representation improves, but the processing time increases
Solution Approach 1:
The patent applies preliminary action by pre-defining standardized appearance style elements and attribute categories before the actual visualization generation process. The system establishes a library of approved visual attributes (colors, line styles, thicknesses, endmarks) and their combinations in advance. During iterative determination of visual identification indicia, the system selects from these pre-established options rather than creating new attributes, which maintains precision in relationship representation while reducing processing time through reuse of predefined elements.
Data Source
AI summary
A computer distinguishes relationships among concepts of conveyance contained within delivered content. The computer receives several of concepts of conveyance and determines a first visual identification indicia for a first of the concepts, with the first visual identification indicia being characterized by a first combination of appearance style elements selected from a group of visual attribute categories. The appearance style elements have sufficient visual contrast relative to one another to represent distinguishable relationships among individual concepts of conveyance, pairs of concepts of conveyance and multiple concepts of conveyance that are overlapping. The computer iteratively determines a visual identification indicia for each concepts of conveyance. The visual identification indicia are characterized by a unique corresponding combination of appearance style elements selected from the visual attribute categories. The computer presents a visualization of concepts of conveyance in a manner that distinguishes relationships among the concepts of conveyance.