Information Processing for Natural-Language Requirement Structuring
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Solution Overview
Problem
Existing systems struggle with generating accurate requirement definitions, often resulting in contradictions or lacking information due to inexperienced engineers, which hampers effective system development.
Innovation Solution
An information processing apparatus and method that acquires and structures requirement information candidates from natural language input, and concretizes them using a structuring and concretization control means to generate feasible design information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If requirement information is generated by inexperienced engineers, then the generation process can be completed, but the requirement definition contains contradictions or lacks information
Solution Approach 1:
The patent introduces an information processing apparatus as an intermediary between the engineer and the requirement definition. This apparatus automatically generates multiple requirement information candidates from input conditions, structures them using classification information, and presents them to the engineer for selection. This mediator eliminates the need for engineers to manually create requirements from scratch, thereby maintaining productivity while significantly improving the accuracy and consistency of requirement definitions.
Solution Approach 2:
The system enables self-service by automatically generating structured requirement information candidates based on input conditions and classification information. The apparatus performs the complex task of requirement formulation autonomously, including generating multiple candidates, structuring them according to predefined classifications, and organizing them into coherent requirement definitions, thereby compensating for the engineer's inexperience without requiring additional manual effort.
2Reliability
If multiple requirement information candidates are generated and structured, then the accuracy of requirement definition is improved, but the processing complexity increases
Solution Approach 1:
The patent segments the requirement generation process into distinct functional modules: an automatic generation unit that creates requirement information candidates, a structuring unit that organizes candidates using classification information, and a presentation unit that displays structured candidates to the engineer. This segmentation allows each module to perform its specific function independently, managing complexity through modular design while enabling accurate requirement definition through systematic processing of multiple candidates.
Solution Approach 2:
The system manages complexity by changing the parameter of structure organization rather than increasing processing complexity. Classification information is used to systematically organize requirement information candidates into predetermined categories, transforming an unstructured set of candidates into a well-organized requirement definition. This parameter change from unstructured to structured organization improves accuracy without proportionally increasing processing complexity.
3Reliability
If structured requirement information candidates are concretized, then feasible design information is provided, but the processing time increases
Solution Approach 1:
The patent applies preliminary action by pre-defining classification information and candidate structures before the actual requirement definition task. The system prepares multiple requirement information candidates in advance with various possible interpretations and structures, so that when an engineer provides input conditions, the system can quickly select and present appropriate pre-structured candidates rather than creating everything from scratch. This preliminary preparation reduces processing time while maintaining feasibility through structured concretization.
Data Source
AI summary
An information processing apparatus includes a structuring control means and a concretization control means. The structuring control means acquires request information described in a natural language, generates at least one or more requirement information candidates based on the acquired request information, and structures the generated at least one or more requirement information candidates. The concretization control means concretizes the at least one or more structured requirement information candidates.