Content Repository Replication via Usage Pattern Monitoring
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Solution Overview
Problem
Large content stores pose challenges for users with limited storage capacity or network bandwidth, as replicating the entire repository is impractical, and selecting relevant content items for replication becomes increasingly difficult as the repository grows.
Innovation Solution
A computer-implemented method and system that monitors usage patterns, determines preferred relationship patterns, and selects content items for replication using a pattern recognition engine, ontology manager, and ontological graph builder to identify and store commonly accessed items and their relationships, enabling efficient replication of a portion of the content repository.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the entire content store is replicated to a portable storage device, then access to all content items is enabled, but the storage capacity requirement becomes prohibitively large
Solution Approach 1:
The patent extracts only the necessary content items and their interrelationships from the entire content store, rather than replicating everything. The system identifies and extracts a subset of content items that form a coherent knowledge structure, enabling portable access while minimizing storage requirements.
Solution Approach 2:
The patent segments the content store into a manageable subset of content items that are selected for replication. By dividing the large content store into smaller, relevant segments based on usage patterns and relationships, the system enables portable access without requiring the entire content store.
2Quantity of substance
If individual content items are selected for replication, then storage capacity is reduced, but determining which items to select becomes increasingly difficult as the repository grows
Solution Approach 1:
The system performs self-service by automatically analyzing usage patterns and content relationships to determine what to replicate. The pattern recognition engine monitors usage behavior and the ontology manager identifies relationships, allowing the system to autonomously select content items without manual intervention.
Solution Approach 2:
The patent implements feedback mechanisms where the pattern recognition engine continuously monitors usage patterns and feeds this information back to the replication engine. This feedback loop enables the system to learn from user behavior and automatically adjust its replication decisions, making the selection process simpler and more accurate over time.
3Loss of information
If a large content store is accessed over a network, then comprehensive information is available, but network bandwidth requirements become excessively high
Solution Approach 1:
The patent applies preliminary action by pre-identifying and pre-replicating the most relevant content items before they are needed. The system analyzes usage patterns and relationships in advance, creating a pre-selected subset that can be accessed locally, thereby avoiding the need for high-bandwidth network transfers when content is actually needed.
Data Source
AI summary
A computer-implemented method for selecting a portion of a content repository for replication including monitoring a usage pattern of a content repository, determining one or more preferred relationship patterns for replication in response to the usage pattern, identifying content items of the content repository matching the preferred relationship patterns, and selecting the identified content items of the content repository. Monitoring the usage pattern is performed by a pattern recognition engine operating on a computer. The content repository includes two or more content items. The relationship patterns are associated with an ontology describing relationships between content items in the content repository.