Relevance-Based Graphical Message Organization
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Solution Overview
Problem
Current message organization tools in online forums and email systems lack effective visual aids to convey the relevance of message originators to recipients, leading to cluttered and less intuitive message displays.
Innovation Solution
A graphical representation system that uses relevance scores to position message originators and their messages relative to the focal user, employing comics-like or graphic novel-style displays with avatars and balloons, and dynamic filtering to prioritize relevant content based on user-defined thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If messages are organized using traditional sorting methods (time, keywords), then message organization is maintained, but user comprehension of message relevance is reduced and displays become cluttered
Solution Approach 1:
The patent transitions from one-dimensional message organization (chronological or keyword-based lists) to a two-dimensional spatial representation where messages are positioned based on relevance scores. The visual display uses spatial relationships (distance, grouping, positioning) to encode relevance information, allowing users to comprehend message importance through visual cues rather than traditional linear sorting.
Solution Approach 2:
The patent employs visual attributes including color coding to indicate message relevance and originator importance. Different colors or shading intensities represent different relevance levels, enabling users to quickly distinguish important messages from less relevant ones without reading content, thus reducing information loss while maintaining organization.
2Loss of information
If all messages are displayed to ensure completeness, then no information is lost, but visual clutter increases and user focus is diluted
Solution Approach 1:
The patent applies local quality by differentiating the visual presentation of messages based on their relevance characteristics. High-relevance messages receive prominent visual treatment (larger size, brighter color, central positioning) while low-relevance messages are subdued or minimized. This allows the display to maintain completeness while using varying visual qualities to guide user attention and reduce perceived clutter.
Solution Approach 2:
The patent implements filtering mechanisms that can selectively display only messages above certain relevance thresholds. While the full message set remains accessible, the default view applies partial action by showing only the most relevant messages, reducing visual complexity. Users can adjust thresholds to reveal more messages when needed, balancing completeness against display simplicity.
3Productivity
If relevance-based visual indication is implemented, then message prioritization is improved, but system complexity increases
Solution Approach 1:
The patent implements self-service by enabling the system to automatically calculate relevance scores and generate visual representations without requiring manual user intervention. The system autonomously analyzes message content, originator relationships, and contextual factors to determine relevance, then automatically positions and styles messages accordingly. This automation improves productivity while the complexity is managed through algorithmic processing rather than manual system configuration.
Data Source
AI summary
Messages to a focal user are organized by relevance of the message originators. A visual representation of the messages includes a focal user representation (textual or graphic) and multiple contact representations (textual or graphic). The contact representations are displayed at respective relevance distances from the focal user representation. Text regions present the contents of messages from the source contacts, e.g., using graphic novel-style word balloons. The contact representations can be positioned on screen in maps, radar format, or other configurations. Users can filter contacts according to relevance, and can filter messages by pertinence.