Knowledge Correlation System Using Node Decomposition
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current searching techniques fail to effectively identify and construct knowledge correlations across various sources of information, limiting the discovery of new information linkages and understanding.
Innovation Solution
A method that decomposes information from sources into nodes, which are then linked to form correlations, allowing users to input terms to explore additional knowledge by constructing knowledge bridges across multiple data structures such as computer file systems, the Internet, relational databases, and ontologies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional search engine techniques are used to identify information about terms, then search results can be obtained through indexing and Boolean logic, but knowledge correlations and new information linkages cannot be effectively identified or constructed
Solution Approach 1:
The patent segments information from multiple sources into discrete nodes, which are then stored in a node pool. This segmentation enables the system to reconstruct knowledge correlations by linking nodes together, thereby recovering information linkages that traditional search engines fail to identify while maintaining efficient information processing capability
Solution Approach 2:
The patent introduces a knowledge correlation construction mechanism as an intermediary between traditional search and information discovery. This intermediary decomposes search results into nodes, stores them in a node pool, and reconstructs knowledge correlations by linking nodes, thereby bridging the gap between conventional search capabilities and advanced knowledge discovery requirements
2Loss of information
If information from multiple sources is processed to construct knowledge correlations, then new knowledge and information linkages are discovered, but system complexity increases due to node decomposition and correlation construction
Solution Approach 1:
The system segments complex information processing into distinct modules: information decomposition into nodes, node storage in a pool, and correlation construction by linking nodes. This segmentation reduces system complexity by making each module independent and manageable while preserving the ability to discover information linkages
Solution Approach 2:
The node pool automatically stores and manages decomposed nodes from multiple information sources. The system self-organizes information into reusable node units that can be automatically linked to construct knowledge correlations, reducing the need for complex manual management while maintaining comprehensive information linkage capability
Data Source
AI summary
Techniques for identifying knowledge use an graphical user interface for inputting one or more terms to be explored for additional knowledge. Then a search is conducted across one or more sources of information to identify resources containing information about or information associated with said terms. The resources are decomposed into elemental units of information and stored in a data structures called nodes. A group of nodes are stored in a node pool and, from the node pool, correlations of nodes are constructed that represent knowledge.