Knowledge Graph Traversal Interface for Reliable Service Linkage Analysis

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing spreadsheet-based systems for managing complex enterprise organizational structures face challenges with data integrity, scalability, security, and data analysis, particularly in tracking linkages between service providers, receivers, and component providers, leading to inefficiencies and increased risk due to human error and lack of data visualization tools.

Innovation Solution

A knowledge graph-based system is employed to semantically link and analyze data, using a semantic ontology to generate triples and visualize relationships between entities, enabling efficient data management and analysis through a user interface that allows for graph-based data traversal.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If a spreadsheet-based system is used to track service linkages, then ease of operation is maintained, but data integrity and reliability deteriorate due to human error

Engineering Contradiction:

Improveease of operationVSAvoiddata integrity

Core Design Contradiction:

Ease of operationVSReliability

Solution Approach 1:

The patent replaces the mechanical/spreadsheet-based data tracking system with an automated knowledge graph system. The knowledge graph automatically traverses and validates service linkage data through structured queries, eliminating manual data entry and human error while maintaining ease of use through automated processes.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The knowledge graph system performs self-validation and self-traversal of service linkages without requiring manual intervention. The system automatically queries its own structured data to verify relationships between services, providers, and receivers, ensuring data integrity through self-service mechanisms.

Inventive Principle:

Principle #25Self-service

2Device complexity

If a spreadsheet-based system is used, then device complexity is low, but data analysis capability and measurement precision worsen

Engineering Contradiction:

Improvedevice complexityVSAvoiddata analysis capability

Core Design Contradiction:

Device complexityVSMeasurement precision

Solution Approach 1:

The patent transitions from two-dimensional spreadsheet tables to a multi-dimensional knowledge graph structure that captures hierarchical relationships between services, providers, and receivers. This dimensional expansion enables sophisticated data analysis capabilities while maintaining manageable system complexity through structured organization.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

Solution Approach 2:

The knowledge graph segments data into distinct, well-defined entities (services, service providers, receivers) with explicit relationship types. This segmentation enables precise data analysis by allowing the system to query and analyze specific relationships independently, improving measurement precision without overwhelming complexity.

Inventive Principle:

Principle #1Segmentation

3Reliability

If a knowledge graph system is implemented, then data integrity and reliability are improved, but device complexity increases

Engineering Contradiction:

Improvedata integrityVSAvoiddevice complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The knowledge graph system serves multiple functions simultaneously: it stores service linkage data, validates data integrity, performs automated traversal queries, and provides structured analysis capabilities. This multi-functionality consolidates what would otherwise require multiple separate systems into a single unified platform, managing complexity through functional integration.

Inventive Principle:

Principle #6Universality (Multi-functionality)

4Ease of manufacture

If manual data tracking is used, then ease of manufacture is high, but productivity and loss of time worsen due to inefficiencies

Engineering Contradiction:

Improveease of manufactureVSAvoidproductivity

Core Design Contradiction:

Ease of manufactureVSProductivity

Solution Approach 1:

The knowledge graph pre-structures service linkage data during the initial setup phase, establishing clear relationships between services, providers, and receivers. This preliminary organization eliminates the need for manual data tracking and validation in subsequent operations, significantly improving productivity while maintaining ease of implementation through automated processes.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20250335461A1User interfaces for data traversal of knowledge graphs

Publication Date: 2025.10.30 WELLS FARGO BANK NA

AI summary

A method may include presenting a user interface on a computing device, the user interface including: a service provider input element identifying a service provider; a service identifier input element identifying a service; and a graph presentation area; executing a knowledge graph database query using a combination of the service provider and the service as input to a knowledge graph database; receiving tuple results in response to the executing, the tuple results including an allocation value property of the service provider attributable to the service provider with respect to the service; and generating in the graph presentation area, an interactive graph based on the tuple results including: representations of entities including the service provider and the service in the tuple results as nodes in the interactive graph, wherein a representation of the service provider includes the allocation value; and links connecting the representations of entities.