Automated Data Potency Scoring for Unbiased Record Structuring
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for analyzing and structuring data records are manual, time-consuming, prone to errors, and lack a neutral party for verification, leading to potential biases and reduced credibility in decision-making processes.
Innovation Solution
A system and method utilizing a server arrangement to extract data records from public sources, identify classes, calculate data potency scores based on specific parameters, tag and process records into a uniform format, and store them as structured data, providing an automated and unbiased analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual analysis of data records is performed, then flexibility and adaptability in analysis approach are maintained, but time consumption and manual effort increase significantly
Solution Approach 1:
The system enables automated self-service analysis of data records through server arrangement that automatically extracts, classifies, scores, and structures data without requiring manual human intervention for each analysis task, thereby reducing time consumption while maintaining operational flexibility through programmable analysis parameters
2Reliability
If manual analysis of data records is performed, then human judgment and interpretation are applied, but errors and inconsistencies increase
Solution Approach 1:
The patent replaces manual human analysis with an automated server arrangement that uses consistent algorithmic processes for data extraction, classification, and scoring, eliminating human errors and inconsistencies while maintaining reliability through standardized evaluation criteria and reproducible analysis methods
3Productivity
If data records are analyzed without a neutral party, then analysis speed is maintained, but credibility and authenticity of results decrease
Solution Approach 1:
The server arrangement acts as a neutral intermediary party between data sources and analysts, automatically extracting and evaluating data records without human bias or conflict of interest, thereby maintaining analysis speed while enhancing credibility and authenticity of the results through independent, standardized evaluation
4Measurement precision
If comprehensive parameter analysis is performed on each data record, then data potency score accuracy is improved, but computational complexity and processing time increase
Solution Approach 1:
The system segments the data analysis process into distinct modular stages: data extraction, classification by record type, parameter identification, scoring calculation, and result structuring. This segmentation allows comprehensive parameter analysis to be performed systematically on each segment, improving score accuracy while managing computational complexity through organized, step-by-step processing
Data Source
AI summary
Disclosed is a system for analyzing and structuring data records, wherein the system comprises a server arrangement operable to: extract data records from publicly available data sources; identify a class of each of the data records; analyze one or more parameters related to each of the data records to calculate a data potency score for each of the data records, wherein the one or more parameters that are analyzed for a data record are selected based on the class of the data record; tag the data potency score with data record corresponding thereto; process the data records with corresponding tagged data potency scores into a uniform format; and store the processed data records in a database arrangement as structured data records.