Network Interoperability via Semantic Value Metrics
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Solution Overview
Problem
Current systems lack effective interoperability between participants in networks, particularly in creating and maintaining value networks where participants can adapt to maximize value metrics, and there is no precise notion of 'value' in existing semantic web frameworks.
Innovation Solution
The implementation of semantic models and matchmaking devices that determine and modify value metrics by directing information flow between participants based on their semantics, enabling automatic and dynamic interoperability and optimization within value networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If semantic models and matchmaking devices are implemented to enable dynamic interoperability between network participants, then the adaptability and value optimization of the network improve, but the device complexity and implementation difficulty increase
Solution Approach 1:
The patent introduces semantic models as intermediary representations that capture the meaning, capabilities, and requirements of network participants. These semantic models act as mediators between diverse participants, enabling automatic matchmaking without requiring complex point-to-point integration logic. The semantic models standardize participant descriptions, allowing the matchmaking device to operate with reduced complexity despite serving diverse participants.
Solution Approach 2:
The matchmaking device implements feedback mechanisms where value metrics are continuously evaluated and used to refine information flow directions. The system monitors the performance of matched participant pairs and adjusts future matchmaking decisions based on observed value creation. This feedback loop enables the system to learn and improve automatically, reducing the need for manual configuration and complex decision logic.
2Productivity
If value metrics are dynamically determined and modified through multiple iterations, then the productivity and value optimization of the network improve, but the loss of time for computation and iteration increases
Solution Approach 1:
The patent performs preliminary actions by pre-defining semantic models for network participants that encode their capabilities, requirements, and value contributions. These semantic models are prepared in advance, allowing the matchmaking device to quickly evaluate potential participant pairings without performing complex analysis during runtime. The preliminary structuring of participant information enables rapid iteration of value metric determination.
Solution Approach 2:
The system implements partial iteration by determining value metrics for subsets of participants in successive stages rather than computing all possible combinations simultaneously. The matchmaking device processes participant matchings in batches, refining value metrics incrementally. This approach achieves near-optimal value optimization with significantly reduced computation time compared to exhaustive evaluation of all participant combinations.
3Measurement precision
If information flow is directed based on semantic models and value metrics, then the reliability and precision of interoperability improve, but the difficulty of detecting and measuring semantic compatibility increases
Solution Approach 1:
The patent transforms abstract semantic concepts into measurable parameters by defining specific attributes within semantic models, such as data formats, communication protocols, and value metric quantifications. These parameterized representations of semantic properties enable automated comparison and matching. The matchmaking device measures semantic compatibility by evaluating these defined parameters rather than attempting to assess abstract semantic meaning, significantly reducing measurement difficulty while maintaining precision.
Data Source
AI summary
Interoperability is enabled between participants in a network by determining values associated with a value metric defined for at least a portion of the network. Information flow is directed between two or more of the participants based at least in part on semantic models corresponding to the participants and on the values associated with the value metric. The semantic models may define interactions between the participants and define at least a portion of information produced or consumed by the participants. The determination of the values and the direction of the information flow may be performed multiple times in order to modify the one or more value metrics. The direction of information flow may allow participants to be deleted from the network, may allow participants to be added to the network, or may allow behavior of the participants to be modified.