Cooccurrence Data Element Selection for Screening Accuracy
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Solution Overview
Problem
In data extraction processes, the initial screening often misses relevant data due to deficiencies in the key elements used, leading to decreased accuracy in identifying data that meets specific extraction conditions.
Innovation Solution
A computer system that selects cooccurrence data elements near a given key element, calculates their importance based on frequency and appearance across multiple data sets, and presents them to users to enhance the initial screening process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If heuristically selected key elements are used for first screening, then the screening process can be performed efficiently, but data meeting extraction conditions may be missed due to key element deficiency
Solution Approach 1:
The system performs preliminary action by automatically selecting candidate key elements from data elements that cooccur with the given key element in the data sets, before the reviewer conducts the second screening. This preliminary selection of complementary key elements ensures that no potentially relevant data is missed during the first screening phase, thereby improving both the efficiency and reliability of the overall screening process.
2Reliability
If more key elements are added to compensate for deficiencies, then data extraction accuracy improves, but the complexity of the screening process increases
Solution Approach 1:
The system applies self-service by automatically selecting candidate key elements based on cooccurrence analysis of the data sets, without requiring manual intervention to identify and add complementary key elements. The controller automatically calculates importance degrees and presents candidate key elements to the user, reducing the complexity burden while maintaining high data extraction accuracy.
3Reliability
If manual selection of key elements is performed, then key element quality improves, but the time and cost of the screening process increases
Solution Approach 1:
The system replaces the manual mechanical process of key element selection with an automated computational system. The controller automatically analyzes data sets, identifies cooccurring data elements, calculates their importance degrees using occurrence frequencies, and presents candidate key elements to the user. This substitution of automated information processing for manual selection significantly reduces the time and cost while maintaining or improving key element quality through systematic cooccurrence analysis.
Data Source
AI summary
An object is to efficiently generate a list of data elements that complement a given key element. A computer includes a memory and a controller, wherein the memory stores data, and the controller performs: selection processing of selecting data elements in vicinity of a predetermined data element as cooccurrence data elements; calculation processing of calculating a degree of importance of each cooccurrence data element; and presentation processing of presenting the cooccurrence data elements.