Modifiable Data Network for Unstructured Artifact Analysis
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Solution Overview
Problem
Current data mining techniques struggle to efficiently extract and summarize key elements and their relationships from unstructured data, limiting the ability to modify data networks based on frequency and importance, making it difficult for users to gain a clear understanding of facts and trends.
Innovation Solution
A method for analyzing data in artifacts to extract key elements, identify relationships, determine frequencies, and create a modifiable data network that allows users to modify key elements, relationships, and their frequencies, enabling classification and modification of the data network based on these factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional data mining techniques are used to extract key elements from unstructured data, then data processing can be performed, but the ability to modify and analyze data networks based on frequency and importance is limited
Solution Approach 1:
The patent implements a dynamic data network where key elements, relationships, and frequencies can be modified in real-time based on user interactions and analysis requirements. The system allows dynamic addition, removal, and reconfiguration of nodes and edges in the data network, enabling adaptability without requiring complete system redesign.
Solution Approach 2:
The patent segments the data network into distinct components: key elements (nodes), relationships (edges), and frequency metrics. This segmentation allows independent modification of each component, enabling versatile data network adjustments while managing complexity through modular organization of data structures.
2Loss of information
If comprehensive data analysis including relationships and frequencies is performed, then better knowledge discovery is achieved, but the complexity of data processing increases
Solution Approach 1:
The patent extracts and separates relationship metadata and frequency information from the main data processing flow, storing them as distinct attributes in the data network structure. This extraction allows comprehensive information capture while simplifying processing by organizing complex data into manageable, queryable components.
Solution Approach 2:
The patent adds dimensional layers to the data network by incorporating frequency dimensions and relationship types alongside traditional key element connections. This multi-dimensional structure enables comprehensive information representation while providing structured access paths that reduce processing complexity through organized data retrieval.
3Measurement precision
If manual analysis of large datasets is performed to identify prominent trends, then detailed understanding is achieved, but time consumption increases significantly
Solution Approach 1:
The patent replaces manual mechanical analysis with automated computational processing of the data network. Algorithms automatically traverse the network structure, calculate frequencies, identify relationships, and extract trends, achieving precise analysis without human time investment while maintaining accuracy through systematic processing.
Solution Approach 2:
The patent implements feedback mechanisms where the data network structure and frequency information continuously inform and refine the analysis process. The system uses accumulated frequency data and relationship patterns to automatically adjust analysis priorities and focus, enabling rapid identification of prominent trends through iterative, self-refining processing.
Data Source
AI summary
Computer-implemented systems, methods, and computer-readable media for analyzing data in one or more artifacts and creating a modifiable data network includes: extracting the key elements from the one or more artifacts; identifying relationship among the key elements for each of the one or more artifacts; determining a first frequency of each of the key elements; determining a second frequency for each relationship among the key elements; creating a data network showing the key elements and the relationship among the key elements; and enabling a user to modify the data network based on one or more of: the key elements; the relationship among the key elements; the first frequency; and the second frequency.