Repertory Grid System for User Requirement Extraction
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Solution Overview
Problem
Current requirement engineering techniques for self-adaptive systems lack effective methods for eliciting user requirements considering various contexts and introducing flexibility in system behavior, particularly due to the complexity of representing user needs using systematic methods.
Innovation Solution
The use of a cognitive interviewing technique called Repertory Grid (RG) to extract user requirements and perform variability analysis, generating supporting means for smart home, smart grid, and automatic driving systems by obtaining and analyzing context information related to user preferences and environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If systematic requirement elicitation methods are used, then requirements can be structured and analyzed, but it becomes difficult for users to represent their requirements due to complexity
Solution Approach 1:
The patent introduces an intermediary system that translates natural language user inputs into structured requirement representations. The system acts as a mediator between the user's intuitive expression and the formal requirement structure, automatically performing analysis and structuring without requiring the user to manually navigate complex systematic methods.
2Adaptability or versatility
If variability acquisition is performed based on goal-based approach, then variability can be discovered from goals, but it presumes strong cognitive ability of interested parties to support intended complexities
Solution Approach 1:
The system performs self-service by automatically conducting variability analysis and goal decomposition without requiring the user to manually perform complex cognitive tasks. The apparatus autonomously analyzes user inputs, identifies goals, and extracts variability information, thereby reducing the cognitive burden on interested parties while maintaining comprehensive variability acquisition.
3Measurement precision
If context information is comprehensively obtained, then user needs can be accurately understood, but the amount of information to be processed increases
Solution Approach 1:
The patent extracts only the essential context information needed for accurate requirement understanding while filtering out redundant data. The system selectively identifies and extracts relevant contextual factors from user inputs, performing extraction of key features and eliminating unnecessary information to maintain accuracy without overwhelming information quantity.
Data Source
AI summary
The present invention suggests need supporting means generating apparatus and method which extract requirements from a user using a repertory grid which is a cognitive interview technique to generate supporting means thereof. The need supporting means generating apparatus of the present invention includes: a question message generating unit which generates at least one question message related with predetermined context information; an answer message obtaining unit which obtains at least one answer message with respect to the question message; a feature information extracting unit which extracts at least one feature information related with the context information based on the answer message; and a supporting means generating unit which generates at least one supporting means to support needs of a user based on the feature information.