Knowledge Graph Visualization for Service Linkage Management
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current spreadsheet-based systems for managing linkages between service providers, service receivers, and component service providers face issues with data integrity, scalability, security, and analysis, particularly when dealing with complex relationships and large datasets, leading to difficulties in compliance, risk management, and decision-making.
Innovation Solution
Implementing a knowledge graph data structure that semantically links and analyzes data, enabling efficient management and visualization of relationships between legal entities, using a knowledge graph application server and client device components to generate and query a knowledge graph database.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a spreadsheet is used to manage linkages between service providers, service receivers, and component service providers, then the system is simple to implement and operate, but the system lacks scalability, data integrity, and security when dealing with complex relationships and large datasets
Solution Approach 1:
The patent replaces the mechanical spreadsheet system with a knowledge graph data structure that uses semantic relationships and graph theory to represent and query complex service provider linkages. This substitution enables scalable handling of large datasets while maintaining ease of operation through intuitive visual interfaces and automated relationship discovery.
Solution Approach 2:
The system transforms the data structure from flat spreadsheet rows and columns to a multi-dimensional graph structure with nodes, edges, and semantic properties. This parameter change in data organization enables the system to handle complex relationships and large volumes of data while preserving operational simplicity through automated querying and visualization.
2Ease of manufacture
If a spreadsheet is used to track service linkages, then the implementation is straightforward, but the system cannot effectively analyze complex relationships and large datasets
Solution Approach 1:
The patent replaces manual spreadsheet analysis with automated knowledge graph processing that uses semantic relationships to efficiently analyze complex service provider linkages. The system automatically queries and visualizes relationships across large datasets, dramatically improving data analysis productivity while keeping implementation straightforward through standardized interfaces.
Solution Approach 2:
The knowledge graph system performs self-service data analysis by automatically discovering and visualizing relationships between service providers, service receivers, and component service providers. This eliminates the need for manual data manipulation while maintaining ease of implementation through automated relationship extraction and presentation.
3Device complexity
If a spreadsheet-based system is used, then the system is simple to deploy, but it lacks security and data integrity controls
Solution Approach 1:
The patent replaces the vulnerable spreadsheet system with a knowledge graph architecture that inherently provides data integrity through semantic relationship validation and consistent data modeling. The system maintains simplicity by using standardized graph data structures while achieving improved reliability through automated relationship verification and controlled access mechanisms.
4Ease of manufacture
If spreadsheets are used to manage service provider relationships, then the initial setup is simple, but the system becomes difficult to navigate and understand as data grows
Solution Approach 1:
The patent transitions from two-dimensional spreadsheet views to multi-dimensional knowledge graph visualizations that display service provider relationships in intuitive spatial arrangements. This dimensional change enables easy navigation of complex relationships while maintaining simple setup through automated graph generation from existing data sources.
Data Source
AI summary
A method may include receiving a login request including a user identifier; accessing a role in a user account associated with the user identifier; presenting a user interface, the user interface including: a service receiver input element presenting a selected service receiver; a service identifier input element presenting a selected service identifier; a graph presentation area; and graph visualization options based on the role in the user account; executing a knowledge graph database query to a knowledge graph database using a combination of the selected service receiver and the selected service identifier; and generating, in the graph presentation area an interactive graph based on tuple results of the knowledge graph database query, the interactive graph including: representations of entities in the tuple results including the selected service receiver and the selected service identifier; and links connecting the representations of entities.