Content Graph Data Structure for Document Collaboration
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Solution Overview
Problem
Conventional methods for representing electronic documents and related information inefficiently use storage and processing resources, making it difficult to exploit this information effectively.
Innovation Solution
A content graph data structure is introduced, where a document is represented with a root node connected to content nodes via 'has Content' edges, and additional nodes for feedback, edits, and comments are created with specific edge types to store and manage proposed edits, comments, and feedback, allowing for efficient storage and retrieval of document-related information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional methods are used to represent electronic documents and related information, then storage and processing resources are consumed, but the efficiency is poor and information exploitation is difficult
Solution Approach 1:
The patent segments document information into distinct node types (content nodes, edit nodes, feedback nodes, comment nodes) within a graph structure. Each node type represents a specific aspect of document information, allowing for organized storage and efficient retrieval. This segmentation enables the system to handle complex document collaboration data without excessive resource consumption while improving information exploitation efficiency.
Solution Approach 2:
The patent transitions from conventional flat or hierarchical document representations to a graph-based multi-dimensional structure. By introducing multiple node types and edge relationships, the system creates additional dimensions for organizing document information (content, edits, feedback, comments as separate dimensions), enabling more efficient information exploitation without linearly increasing storage requirements.
2Ease of operation
If a detailed graph structure with multiple node types is created to store document information, then information usability is improved, but data structure complexity increases
Solution Approach 1:
The patent uses standardized node types as intermediaries between the raw document data and the user interface. Each node type (content, edit, feedback, comment) serves as a mediator that structures information in a way that is easy to query and display. This intermediary layer simplifies information usability while managing complexity through consistent node type definitions and relationship patterns.
Solution Approach 2:
The patent creates a universal graph structure where the same node and edge types can represent various document information elements. The content nodes, edit nodes, feedback nodes, and comment nodes serve multiple functions across different document operations and collaboration scenarios. This universality reduces data structure complexity by reusing the same structural patterns rather than creating specialized structures for each information type.
Data Source
AI summary
A content graph data structure representing at least a portion of a document is provided. The data structure includes a first node containing contents authored by a first user. The data structure further includes a second node specifying a proposed edit to the contents of the first node proposed by a second user distinct from the first user, the second node being connected to the first node using an edge of a first type, the edge of the first type connoting that the edit specified by the second node is proposed for the first node, such that the data structure is accessible to identify the second node as specifying an edit proposed for the first node.