Knowledge Graph Property Tracking for Automated Ontology Updates
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Solution Overview
Problem
Current techniques for developing ontologies are time-consuming and prone to errors, such as failing to identify relevant semantic concepts or outdated concepts, leading to inconsistent and inefficient ontology management.
Innovation Solution
A method for maintaining ontologies by tracking the use of properties over time, including techniques for changing property status based on counts of properties in electronic documents, and processing documents using updated property statuses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual ontology creation and updates are performed, then ontology accuracy can be maintained, but the process becomes extraordinarily time-consuming and labor-intensive
Solution Approach 1:
The system enables automatic ontology maintenance by having the ontology itself serve its own update needs through automated property status changes based on document usage counts, eliminating the need for manual intervention in routine ontology updates
Solution Approach 2:
The patent replaces manual mechanical processes of ontology creation and updates with automated computational processes that analyze document counts and automatically adjust property statuses, transforming a manual task into an automated system
2Reliability
If manual ontology updates are performed, then conceptual accuracy can be maintained, but errors occur such as failing to identify relevant semantic concepts or outdated concepts
Solution Approach 1:
The system continuously monitors document usage counts for ontology properties and uses this feedback to automatically adjust property statuses, ensuring that relevant concepts are identified and outdated concepts are removed based on actual usage data rather than manual assessment
Solution Approach 2:
The patent replaces manual conceptual analysis with automated computational detection that processes document counts and automatically identifies relevant versus outdated concepts, eliminating human error in concept detection
3Ease of operation
If manual ontology maintenance is performed, then detailed control over ontology content is maintained, but the process is inefficient and does not scale well
Solution Approach 1:
The ontology system performs its own maintenance automatically by analyzing document usage patterns and adjusting property statuses without requiring manual intervention, enabling the system to maintain itself at scale
Solution Approach 2:
The system automatically changes property status parameters based on document count thresholds, transforming static ontology definitions into dynamic structures that adapt automatically to changing usage patterns and efficiency requirements
Data Source
AI summary
Techniques and solutions are provided for improved use of knowledge graphs in document processing. The relevance of properties to a knowledge graph may change over time. While a property may appear, it may take some time before it is apparent that the property should be used in a knowledge graph. Similarly, while a property may be relevant for a period of time, it can lose its relevance. The present disclosure provides techniques for tracking the use of properties over time, and making or proposing property status changes. These changes can result in making the properties visible or non-visible in a knowledge graph, which in turn can affect how future documents are processed. Further, in some cases a property can be made active, and documents processed when the property was not present or not active can be reprocessed to obtain information for the property.