Conversation-Connected Visualization of Items
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Text-based email communications often lead to cumbersome and frustrating challenges in collaboration, task management, and scheduling due to the need for repeated exchanges and conversion of items into organized documents.
Innovation Solution
A system that provides conversation-connected visualization of items based on a user-created list, where connections between items are determined and represented as nodes, allowing users to define and characterize them within a visualization associated with the communication, enhancing collaboration and information presentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If text-based email communications are used for collaboration and task management, then information can be exchanged between users, but the collaboration process becomes cumbersome and frustrating due to repeated exchanges and the need to convert items into organized documents
Solution Approach 1:
The patent transforms flat text-based email communications into multi-dimensional visual maps that display items, connections, and relationships in spatial dimensions. This dimensional transformation allows users to perceive relationships between items at a glance rather than through sequential text reading, directly addressing the cumbersome nature of text-based collaboration while maintaining information exchange capabilities.
Solution Approach 2:
The patent introduces an intermediary visualization layer between the sender and receiver of email communications. This visual map intermediary automatically extracts items from email text, determines their relationships, and presents them in an organized visual format, eliminating the need for users to manually convert text into structured documents and reducing repeated exchange cycles.
2Loss of information
If text-based email communications are used, then information exchange is possible, but repeated exchanges and conversion of items into documents are required
Solution Approach 1:
The patent performs preliminary action by automatically extracting items and determining their relationships immediately when email text is received, before any user interaction is required. This preliminary processing creates a complete visual representation of all items and their connections in a single pass, eliminating the need for repeated exchanges to ensure information completeness and preventing time loss from multiple conversion cycles.
Solution Approach 2:
The system performs self-service by automatically analyzing email content, identifying items, determining relationships between them, and generating visual maps without requiring user intervention for each extraction and organization step. This automation eliminates the manual time investment required for converting text-based communications into structured information while maintaining complete information representation.
3Ease of operation
If visualizations of items and connections are generated, then collaboration efficiency increases and information is consolidated in a user-friendly format, but computing resource usage increases
Solution Approach 1:
The patent applies partial action by generating visualizations selectively based on user needs and email content complexity rather than creating full visual maps for every communication. The system can generate visualizations at different levels of detail, focusing computational resources on extracting and visualizing only the most relevant items and relationships, thereby reducing overall computing resource usage while maintaining user-friendliness where it matters most.
4Loss of information
If connections between items are determined and visualized as nodes, then relationships between items become clear and collaboration improves, but the complexity of processing and visualizing increases
Solution Approach 1:
The patent segments the complex task of relationship analysis into distinct processing stages: extracting individual items from text, determining binary relationships between pairs of items, and progressively building the visual map. This segmentation breaks down the complex processing into manageable steps, making the system more tractable while still achieving comprehensive relationship visualization that clarifies connections between items.
Data Source
AI summary
Conversation connected visualization of items based on a user created list is provided. In some examples, a user may indicate the entry of a list of items to be visualized or user, intent may be inferred from an entered list in an email or similar communication. Connections between the items on the list may be determined and a connected node visualization generated. The visualization may be presented within a user interface in conjunction with the email and users allowed to define or characterize nodes or items in the visualization. Depending on a type of item, different prompts to provide definition/characterization input may be presented. The visualization may be associated with the communication and a conversation to winch the communication belongs. Users may access the visualization through a separate application or through the communication application.