Group Cooperation Prediction for Measure Recommendation Ranking
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Solution Overview
Problem
Existing organization improvement measures lack specificity and require significant manpower for development, and there is a need to automatically assess cooperation rates among group members when implementing actions.
Innovation Solution
A decision making support device that utilizes a processor and storage device to execute programs for acquiring and predicting cooperation rates among group members through machine learning models, and communicates with multiple computers to correct and transmit action ranks based on member feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a measure is presented based on organization characteristics, then the measure can be tailored to specific organizational needs, but the measure lacks specificity and requires significant manpower to develop
Solution Approach 1:
The patent creates templates for measures that can be copied and adapted to different organizational contexts. Instead of developing custom measures from scratch for each organization, standardized measure templates are created that capture common improvement patterns, reducing development effort while maintaining adaptability through parameter customization.
Solution Approach 2:
The system allows measures to be adapted by changing parameters such as organizational characteristics, industry type, and specific goals. By parameterizing the measures rather than creating entirely custom solutions, the system achieves adaptability without proportionally increasing development complexity.
2Measurement precision
If manual assessment of cooperation rates is performed, then detailed feedback can be obtained, but significant time and resources are required
Solution Approach 1:
The patent replaces manual mechanical assessment processes with automated computational systems. Machine learning models and algorithms automatically analyze organizational data to assess cooperation rates, eliminating the need for time-consuming manual evaluation while maintaining or improving measurement precision through consistent, data-driven analysis.
Solution Approach 2:
The system enables automated self-assessment of cooperation rates by organizations using their own data. The measurement system processes organizational characteristics and measure implementation data automatically without requiring external expert intervention, reducing time investment while providing precise measurements.
3Manufacturing precision
If specific measures are developed for each organization, then the measures can be highly targeted, but the development process requires excessive manpower
Solution Approach 1:
Standardized measure templates serve as reusable copies that can be rapidly deployed across multiple organizations. These templates encapsulate proven improvement patterns and can be customized through parameter adjustment rather than complete redevelopment, achieving high specificity without proportional increases in development productivity.
Solution Approach 2:
The measure templates are designed with universal applicability across different organizational types and contexts. A single measure template can serve multiple organizations by adapting to different parameters, eliminating the need to create entirely new measures for each organization and thereby maintaining specificity while improving development productivity.
Data Source
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AI summary
A decision making support device executes acquisition processing of acquiring a feature value related to a measure to be implemented by a group, a feature value related to an action of the group, and a feature value related to the group, first prediction processing of inputting the feature value related to the measure, the feature value related to the action, and the feature value related to the group, which are acquired by the acquisition processing, to a machine learning model that predicts whether members of the group cooperate with one another to take the action, and outputting a first prediction result of predicting whether the members of the group cooperate with one another to take the action when the feature value related to the action and the feature value related to the group are input according to whether the measure is implemented, and output processing of outputting the first prediction result obtained by the first prediction processing.