Dynamic Data Interrelation Acquisition via Syntactic and Semantic Comparison
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Solution Overview
Problem
Current data processing systems face limitations in acquiring and managing interrelations between data items, particularly in dynamic and user-specific contexts, due to static hierarchical structures and limited search capabilities, which restrict user flexibility and precision in navigating and utilizing data.
Innovation Solution
A method that dynamically acquires interrelations by performing syntactic and semantic comparisons between data items and requests, using a data processing system to create links and log user interactions, enabling flexible and individualized navigation and search optimization through a self-learning mechanism.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static hierarchical structures are used for data organization, then data processing systems can maintain simple and stable data management, but user flexibility and precision in navigating and utilizing data are restricted
Solution Approach 1:
The patent implements dynamic data organization by replacing static hierarchical structures with a system that automatically adjusts data relationships based on user interactions. The system learns from user behavior patterns and dynamically reorganizes data interrelations to optimize navigation and retrieval, thereby improving adaptability without requiring complex manual configuration.
Solution Approach 2:
The system performs self-learning and self-optimization by automatically analyzing user interactions with data and adjusting the data organization structure accordingly. This self-service mechanism eliminates the need for complex manual data management while adapting to user preferences and improving navigation flexibility over time.
2Measurement precision
If limited search capabilities are used, then data processing systems can maintain simple operation, but precision in data retrieval is insufficient
Solution Approach 1:
The patent employs feedback mechanisms where the system continuously monitors user interactions with search results and adjusts the search algorithm accordingly. This feedback loop enables the system to learn from user behavior patterns and improve retrieval precision over time, automatically optimizing search capabilities without requiring complex manual tuning.
Solution Approach 2:
The system dynamically changes search parameters based on user behavior patterns and data context. By automatically adjusting search criteria, weighting, and retrieval algorithms based on learned user preferences, the system achieves high precision in data retrieval while maintaining operational simplicity through automated parameter optimization.
3Measurement precision
If dynamic acquisition of interrelations is implemented, then user-specific data retrieval precision is improved, but system complexity increases
Solution Approach 1:
The system achieves dynamic acquisition of interrelations through self-learning mechanisms that automatically analyze user interactions and construct personalized data relationships. This self-service approach enables high precision in user-specific data retrieval while avoiding the complexity of manual system configuration or complex predetermined rules.
Data Source
AI summary
A method for acquiring an interrelation between an item of data representing an item of information of a data inventory and an item of data representing an item of information of a request for an interrelation to the item of data representing an item of information of a data inventory by means of a data processing system with data representing information in a data inventory which can be accessed via a data source comprises a link being established by means of a syntactic comparison and/or by means of one semantic comparison of the item of data representing an item of information of a data inventory with the item of data representing an item of information of the request for interrelation with the item of data representing an item of information of a data inventory. According to the method, results of requests for an interrelation are grouped according to topics.