Multi-dimensional Parameter Sets for Heterogeneous Data Extraction
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Solution Overview
Problem
Current data extraction techniques are not suitable for all purposes and fail to efficiently process big data applications, necessitating the development of specific methods for data extraction and modeling that can handle heterogeneous data sources effectively.
Innovation Solution
A computer-implemented method that stores named object entities with assigned vectors, reads and processes heterogeneous data sources, calculates and weights occurrences of these entities, and arranges them in a multidimensional data space for efficient processing and control command initialization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If current data extraction techniques are used, then data can be extracted from sources, but the extraction is not efficient for big data applications and not suitable for all purposes
Solution Approach 1:
The patent transforms unstructured text data into structured multi-dimensional parameter sets by changing the representation parameters of the data. Each named entity is converted into a parameter set with multiple dimensions (technical parameters, operational parameters, etc.), enabling efficient processing and adaptation to different application purposes while maintaining versatility.
Solution Approach 2:
The patent introduces an intermediary processing layer that converts heterogeneous data from various sources into a standardized multi-dimensional parameter format. This intermediary transformation layer enables efficient big data processing while maintaining compatibility with different data sources and application requirements.
2Loss of information
If heterogeneous data sources are processed, then comprehensive information can be obtained, but the data processing complexity increases
Solution Approach 1:
The patent segments heterogeneous data into discrete named entities and further divides each entity into structured parameter sets with multiple dimensions. This segmentation approach organizes complex heterogeneous data into manageable, standardized units, reducing processing complexity while preserving information completeness.
Solution Approach 2:
The patent applies parameter transformation to convert unstructured heterogeneous data into structured multi-dimensional parameter sets. By changing the data representation from unstructured text to structured parameters with defined dimensions, the system manages data complexity while maintaining comprehensive information.
3Productivity
If data is transformed into tailored format for specific devices, then processing efficiency improves, but the transformation process becomes more complex
Solution Approach 1:
The patent creates a universal multi-dimensional parameter set structure that can serve multiple devices and applications. By establishing a standardized parameter framework that works across different contexts, the system achieves processing efficiency without requiring complex device-specific transformations, as the same parameter structure serves multiple purposes.
Solution Approach 2:
The patent performs preliminary transformation of heterogeneous data into standardized multi-dimensional parameter sets before data processing. This advance structuring reduces the complexity of subsequent processing operations, as data is already in the required format when needed, improving overall processing efficiency.
Data Source
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AI summary
The present invention is directed towards a computer implemented method for extracting machine readable multi-dimensional parameter sets. The suggested method can rely on heavily heterogeneous data sources, which includes data representation in any type and format. The computer implemented method is able to detect superior information in such data sources and is able to transfer such data into a data format being specifically tailored to specific end devices. Hence, the resulting data can be efficiently processed by further devices and accordingly the suggested method is suitable for big data analysis. The invention is furthermore directed towards a respectively arranged system along with a computer program product and a computer-readable medium.