Interaction Network Analysis via Structured Data Segmentation
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Solution Overview
Problem
Existing methods for analyzing interaction networks, whether through text-based programming or graphic interfaces, face difficulties in expressing and modifying operational conditions due to complexity and irregularity, making it hard to understand and simulate dynamic characteristics effectively.
Innovation Solution
A method and device utilizing a specific data structure that includes a state area, function area, and condition area arranged in series for each node, allowing for the interpretation and updating of node states, with a convergence analyzer determining when to finish the analysis based on state history and convergence criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If text-based programming method is used to computer simulate interaction network, then operational scripts can be written, but it is difficult to read and understand the entire condition due to complexity
Solution Approach 1:
The patent segments the operational scripts into structured blocks with clear delimiters (e.g., '{', '}', '@') that organize information hierarchically. Each node's operational conditions are divided into distinct sections (state definitions, function definitions, condition definitions), making the complex simulation logic readable and manageable while maintaining full automation capability.
2Extent of automation
If text-based programming method is used, then operational conditions can be specified, but it is difficult to modify operational condition due to irregularity and complexity of scripts
Solution Approach 1:
The patent divides operational conditions into modular, independently editable sections (state areas, function areas, condition areas) with clear structural delimiters. This segmentation allows users to modify specific operational parameters without affecting the entire script, significantly improving ease of modification while maintaining automation.
Solution Approach 2:
The patent enables easy modification of operational conditions by allowing direct parameter changes within the structured format. Users can alter state values, function parameters, or condition thresholds by simply editing the relevant numeric or string parameters within the delimited blocks, without needing to understand or rewrite the surrounding script structure.
3Ease of operation
If graphic interface is used to express interaction network, then general connection state can be easily and visually understood, but quantitative correlation and functional relationship are difficult to express
Solution Approach 1:
The patent merges the advantages of both graphic interfaces and text-based programming by using a structured text format that visually represents the network structure (showing node connections and relationships) while simultaneously embedding quantitative data (correlation values, functional parameters, condition thresholds). This combination preserves both visual clarity and numerical precision.
4Ease of operation
If graphic interface is used, then interaction network can be visually expressed, but it is inappropriate for computer simulation due to lack of numerical expression
Solution Approach 1:
The patent transforms the graphic interface representation into a structured text format that maintains visual readability while incorporating all necessary numerical parameters for simulation. The structured format includes explicit numerical values for states, functions, and conditions, making the data directly suitable for computer simulation while preserving the visual structure of the interaction network.
Data Source
AI summary
A method for analyzing an interaction network includes: interpreting input data; and determining states of a plurality of nodes described to the input data based on information acquired by the interpretation of the input data, and updating a state of a system expressed as the interaction network based on the states of the nodes, in which at least one piece of information for describing the states of the nodes is arranged in series in the input data.