Knowledge Graph Marine Assessment Indicators for Objective Scoring
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Solution Overview
Problem
Traditional assessment indicator systems for marine scenarios are subjective, lack objectivity and comprehensiveness, and have poor applicability due to reliance on expert experience, leading to inconsistencies and limited knowledge updates.
Innovation Solution
Construct an assessment indicator system based on a knowledge graph, using multi-source data to extract knowledge, build a spatiotemporal raster database, extend the initial indicator set, establish a directed weighted network with indicators as nodes, and calculate weights using a random walk model to determine comprehensive assessment values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the assessment indicator system is constructed based on experts' experience, then the construction process is simple and fast, but the objectivity and comprehensiveness of the indicator system deteriorates due to subjective bias
Solution Approach 1:
The patent introduces a knowledge graph as an intermediary between expert experience and the assessment indicator system. The knowledge graph objectively stores and structures marine domain knowledge, relationships, and data, serving as a mediator that transforms subjective expert opinions into structured, queryable, and verifiable knowledge representations, thereby improving objectivity while maintaining construction efficiency
Solution Approach 2:
The patent replaces the manual, experience-based mechanical process of indicator system construction with an automated knowledge processing system. By using knowledge graph construction, automated indicator extraction, and algorithm-based weighting, the system substitutes human expert manual work with computational processes, reducing subjective bias while maintaining productivity
2Device complexity
If the assessment indicator system is constructed based on experts' experience, then the construction process is simple, but the consistency and reliability of the indicator system deteriorates due to different expert views
Solution Approach 1:
The patent creates a universal knowledge graph framework that can accommodate multiple expert views and different marine domain knowledge sources. The knowledge graph structure allows various types of knowledge (indicators, relationships, data, rules) to be integrated in a unified manner, enabling consistent processing of diverse expert inputs through standardized knowledge representation and reasoning mechanisms
Solution Approach 2:
The patent implements feedback mechanisms where the knowledge graph continuously refines the assessment indicator system based on accumulated knowledge and data. The system uses the knowledge graph to validate, verify, and adjust indicators, creating a closed-loop process that improves consistency through iterative refinement and knowledge accumulation rather than relying solely on individual expert judgments
3Productivity
If the assessment indicator system is constructed based on experts' experience, then the construction process is simple and fast, but the adaptability and comprehensiveness of the indicator system deteriorates with limited knowledge updates
Solution Approach 1:
The patent transforms the static, fixed indicator system into a dynamic system through the knowledge graph. The knowledge graph can be continuously updated with new marine data, research findings, and changing environmental conditions. The system dynamically adapts by incorporating new knowledge into the graph, which then automatically updates the assessment indicators and their relationships, enabling the system to evolve with emerging knowledge while maintaining construction efficiency
Solution Approach 2:
The patent performs preliminary action by pre-constructing a comprehensive knowledge graph that anticipates future knowledge needs and potential indicator requirements. The knowledge graph is built in advance with structured relationships and data that can be quickly queried and utilized when new assessment needs arise, enabling rapid adaptation without starting from scratch
Data Source
AI summary
A method for constructing an assessment indicator system for typical marine scenarios based on a knowledge graph includes: obtaining multi-source data and an initial indicator set; performing knowledge extraction on the data, and constructing a knowledge graph and a spatiotemporal raster database; extending the initial indicator set based on the knowledge graph to obtain a basic indicator set, and obtaining a relationship between basic indicators and a degree of uncertainty of the relationship; establishing a directed weighted network with indicators as nodes based on the relationship and degree of uncertainty of the relationship, and calculating a weight for each basic indicator using a random walk model; and obtaining an observation value of each basic indicator based on the spatiotemporal raster database, determining an assessment value of a comprehensive indicator using the observation value of each basic indicator and the weight for each basic indicator to form an assessment indicator system.