Semantic Analysis of Confrontation Scenarios via Prioritized Operator Networks
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Solution Overview
Problem
In confrontation scenarios, such as sports or military activities, determining the states of multiple target objects and their relations requires significant manpower, leading to inaccurate analysis results due to missed determinations and high resource consumption.
Innovation Solution
A method and apparatus for semantic analysis based on target-attribute-relation, utilizing a pre-trained analyzing model with operator networks of varying priorities to process triplet data in a graph data structure, enhancing the accuracy of relation determination and updating markers to characterize semantic information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If artificial determination method is used to determine states and relations of target objects, then the analysis can be performed with simple system structure, but the accuracy of determination results deteriorates due to missed determinations and high resource consumption
Solution Approach 1:
The patent segments the complex task of semantic analysis into multiple specialized operator networks, each responsible for specific relation types (e.g., spatial relations, semantic relations). This segmentation allows the system to achieve high accuracy through specialized processing while managing complexity by dividing the overall system into modular, independent components that can be developed and maintained separately.
Solution Approach 2:
The patent introduces a priority dimension to organize operator networks, creating a hierarchical structure where networks are executed in predetermined priority orders. This dimensional organization allows the system to manage complexity by structuring operations vertically (priority levels) while maintaining high accuracy through systematic processing of all relation types across different priority layers.
2Measurement precision
If multiple operator networks with different priorities are introduced to improve analysis accuracy, then the measurement precision improves, but the device complexity increases due to multiple networks and priority management
Solution Approach 1:
The patent applies preliminary action by pre-establishing priority relationships among operator networks before execution. The system pre-processes initial data into triplet data marked in graph structure, and pre-defines the execution order of operator networks based on their priorities. This preliminary organization reduces runtime complexity and enables accurate relation determination through systematic, pre-planned processing sequences.
Solution Approach 2:
The patent introduces an intermediary data structure (triplet data with graph structure and markers) that mediates between raw input data and final analysis results. This intermediary structure standardizes information flow across multiple operator networks, allowing them to interact systematically without direct complex interconnections, thereby managing system complexity while maintaining high determination accuracy.
3Measurement precision
If comprehensive analysis of all relation types is performed to improve accuracy, then the measurement precision improves, but the productivity deteriorates due to increased processing time and resource consumption
Solution Approach 1:
The patent implements periodic action through the priority-based execution sequence of operator networks. Networks are executed in periodic waves according to their priority levels, with higher-priority networks executed first and their results fed into subsequent lower-priority networks. This periodic execution pattern enables comprehensive analysis of all relation types while maintaining processing efficiency through structured, rhythmic processing cycles rather than chaotic sequential evaluation.
Data Source
AI summary
A method includes: pre-processing initial data of an acquired to-be-analyzed confrontation scenario, to obtain triplet data marked in a graph data structure, inputting the triplet data into a pre-trained analyzing model, to determine a result of analysis on semantic information of the to-be-analyzed confrontation scenario; wherein the analyzing model includes a plurality of operator networks that are provided with execution priorities, wherein the plurality of operator networks are configured for analyzing relations of different types; and the processing result of any one of the operator networks includes: in the relation type corresponding to the operator network, respective true relations of all of the node pairs, and confidences and descriptive values of the true relations; and according to the graph data structure that is updated by using the processing results of all of the operator networks, characterizing the result of analysis on the semantic information of the to-be-analyzed confrontation scenario.