Requirement Analysis for Responsible Department Assignment
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Solution Overview
Problem
Existing project management systems lack the ability to efficiently identify and assign responsibilities to relevant departments based on project requirements, making it difficult to create effective implementation plans.
Innovation Solution
A project support system that utilizes a machine learning model, such as a deep learning model, to analyze requirement data and identify responsible departments with high relevance to the project requirements, reducing the need for human intervention and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual methods are used to identify responsible departments for project requirements, then human judgment and flexibility are maintained, but the process becomes time-consuming and labor-intensive
Solution Approach 1:
The patent replaces manual mechanical analysis with an automated machine learning system. The processing unit executes algorithms that automatically analyze requirement data and identify responsible departments, substituting human cognitive work with computational processes. This dramatically increases productivity while reducing the time required for department identification.
Solution Approach 2:
The system enables self-service automation where the machine learning model independently performs the analysis of requirement data and department identification without requiring manual intervention. The processing unit automatically executes the identification process based on input requirement data, making the system self-sufficient in performing the analytical task.
2Measurement precision
If comprehensive analysis of requirement data is performed to accurately identify responsible departments, then identification accuracy improves, but system complexity increases
Solution Approach 1:
The patent employs a universal machine learning model that can handle multiple types of requirement data and identify responsible departments across different project domains. The processing unit executes a general-purpose algorithm that adapts to various input formats and requirements, achieving high accuracy without proportionally increasing system complexity through specialized components for each case.
Data Source
AI summary
A project support system (10) includes at least one processor configured to execute a first process (s1) of acquiring requirement data (100) recording information on a requirement content required in a project, and a second process (s2) of identifying a responsible department that is highly relevant to the requirement content recorded in the requirement data (100).