Document Activity Graphs for User Matching and Task Discovery
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Solution Overview
Problem
Conventional document collaboration tools fail to provide mechanisms for finding qualified people to perform necessary document-related tasks and derive value from information about document-related activities.
Innovation Solution
A software and/or hardware facility manages information about document-related activities using document graphs to represent user interactions and tasks, enabling users to subscribe to each other's activities, aggregate document-related activities, and match users that can help with tasks with those that need help.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional document collaboration tools are used to track user activities, then basic real-time editing visibility is provided, but effective management and communication of document-related activities fails
Solution Approach 1:
The patent segments document-related activities into distinct types (authoring, editing, commenting, feedback, reading) and represents them as separate entities in a document graph. Each activity type can be independently tracked, managed, and communicated through the system, allowing comprehensive activity information management without requiring a monolithic complex system.
Solution Approach 2:
The patent introduces a graph-based dimension to represent document activities, moving beyond traditional linear or tabular representations. The document graph structure enables multi-dimensional relationships between users, documents, and activities to be visualized and managed, providing comprehensive activity tracking while maintaining system organization.
2Productivity
If no specialized matching mechanism is implemented, then all users are equally visible, but qualified users for specific tasks cannot be found efficiently
Solution Approach 1:
The patent implements feedback mechanisms where users can subscribe to specific types of document-related activities from other users. The system provides feedback by notifying subscribers about relevant activities, enabling efficient discovery of qualified users for specific tasks based on their demonstrated expertise and activity patterns.
Solution Approach 2:
Users autonomously declare their capabilities and interests by creating profiles indicating the types of document activities they perform or are interested in. The system automatically matches users based on these self-declared preferences, eliminating the need for manual intervention in the matching process while improving task assignment efficiency.
3Loss of information
If detailed information about all user activities is tracked, then comprehensive activity data is available, but hardware resources are excessive
Solution Approach 1:
The patent extracts and stores only the essential elements of document-related activities in the document graph structure, separating critical activity information from redundant data. By focusing on key attributes (user identity, activity type, document reference, timestamp), the system maintains comprehensive activity tracking while minimizing hardware resource requirements.
Solution Approach 2:
Instead of tracking all possible user actions and filtering for relevant information, the patent inverts the approach by pre-defining specific document-related activity types to track and only capturing those. This selective tracking from the outset reduces data volume and hardware requirements while maintaining information completeness for the defined activity categories.
Data Source
AI summary
A facility for managing information about document-related activities is described. In some cases, the facility uses particular kinds of structures to represent, in a document graph, document-related activities performed by particular users. In some cases, the facility uses these structures to enable one user to subscribe to the document-related activities performed by another user. In some cases, the facility uses these structures to aggregate document-related activities performed by users in a group of users, such as by aggregating topics that are addressed by documents that are the subject of these document-related activities. In some cases, the facility uses particular kinds of structures to represent, in a document graph, tasks that certain users either can help with or need help with. In some cases, the facility uses these structures to match users that can help with a task with users that need help with a task.