Dynamic Data Interrelation Acquisition via Syntactic Semantic Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing 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 restricts user flexibility and precision in data retrieval and synchronization.
Innovation Solution
A method that utilizes syntactic and semantic comparisons to dynamically acquire interrelations between data items, allowing for flexible and individualized navigation and search within data inventories, using a data processing system that integrates search engines and creates keyword indices for relevant document retrieval, enabling precise search queries and full-text searches without replicating data sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static hierarchical structures are used for data organization, then system simplicity is maintained, but user flexibility and adaptability deteriorate
Solution Approach 1:
The patent implements dynamic interrelation acquisition that adapts to user behavior and context. The system transitions from static hierarchical menus to dynamic links that are created based on syntactic and semantic comparisons of data items, allowing the system structure to evolve and adapt to user needs while maintaining manageable complexity through automated processes.
Solution Approach 2:
The system performs preliminary syntactic and semantic analysis of data items to pre-establish potential interrelations. By comparing data items beforehand and creating links based on semantic relationships, the system prepares adaptive navigation paths in advance, enabling user flexibility without requiring complex real-time processing during user interaction.
2Measurement precision
If comprehensive data search capabilities are implemented, then information retrieval precision is improved, but system resource consumption increases
Solution Approach 1:
The patent extracts only the essential syntactic and semantic features from data items that are necessary for establishing interrelations. By comparing only these extracted features rather than processing entire data sets, the system achieves precise search results while minimizing resource consumption through selective analysis of relevant data characteristics.
Solution Approach 2:
The system introduces syntactic and semantic comparison mechanisms as intermediaries between user queries and data retrieval. These intermediaries pre-process and filter data based on linguistic and meaning-based relationships, enabling precise information retrieval without requiring exhaustive search of all data sources, thus reducing overall system resource consumption.
3Reliability
If data replication is performed for synchronization, then data availability is improved, but data inventory size and storage requirements increase
Solution Approach 1:
The patent creates lightweight copies in the form of interrelation links rather than full data replication. The system establishes semantic connections between data items across different sources without duplicating the actual data content, maintaining data availability through referenced links while avoiding the storage overhead of complete data replication.
Solution Approach 2:
The interrelation acquisition mechanism serves multiple functions simultaneously: it enables data synchronization, creates navigation paths, establishes semantic relationships, and provides cross-referencing capabilities. This multi-functionality eliminates the need for separate data replication processes, achieving data availability without increasing inventory size through redundant storage.
4Productivity
If manual interrelation establishment is used, then link accuracy is maintained, but time consumption and operational effort increase
Solution Approach 1:
The system performs self-service interrelation acquisition by automatically comparing data items syntactically and semantically to establish links without manual intervention. The automated comparison processes maintain link accuracy through systematic analysis of data relationships while dramatically increasing productivity by eliminating time-consuming manual operations.
Solution Approach 2:
The system incorporates feedback mechanisms that continuously refine interrelation acquisition based on usage patterns and validation results. By monitoring the effectiveness of automatically created links and adjusting the syntactic and semantic comparison parameters accordingly, the system maintains high link accuracy while operating autonomously at high speed.
Data Source
AI summary
A method for acquiring at least one interrelation between at least one item of data representing at least one item of information of at least one data inventory and at least one item of data representing at least one item of information of a request for an interrelation (interrelation request) to the at least one item of data representing at least one item of information of at least one data inventory by means of a data processing system. Furthermore, a data processing system with data representing information in at least one data inventory that is accessible via at least one data source as well as to a data processing device for electronic data processing comprising a control and/or computing unit, an input unit and an output unit, which are respectively configured and/or adapted for at least partially carrying out a method according to the invention.