Natural Language-Based Conceptual Modelling Frameworks: State of the Art and Future Opportunities

被引:2
|
作者
Hossain, Bayzid Ashik [1 ]
Mukta, Md. Saddam Hossain [2 ]
Islam, Md Adnanul [3 ]
Zaman, Akib [2 ]
Schwitter, Rolf [4 ]
机构
[1] Charles Sturt Univ, Sch Comp Math & Engn, Panorama Ave, Bathurst, NSW 2795, Australia
[2] United Int Univ, Dept Comp Sci & Engn, Madani Ave, Dhaka 1212, Bangladesh
[3] Monash Univ, Fac Informat Technol, Act Lab, Clayton, Vic 3800, Australia
[4] Macquarie Univ, Sch Comp, Balaclava Rd, Sydney, NSW 2109, Australia
关键词
Natural language processing; information extraction; conceptual modelling; knowledge representation; semantic round-tripping; TOOL;
D O I
10.1145/3596597
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Identifying requirements for an information system is an important task and conceptual modelling is the first step in this process. Conceptual modelling plays a critical role in the information system design process and usually involves domain experts and knowledge engineers who brainstorm together to identify the required knowledge to build an information system. The conceptual modelling process starts with the collection of necessary information from the domain experts by the knowledge engineers. Afterwards, the knowledge engineers use traditional model driven engineering techniques to design the system based on the collected information. Natural language-based conceptual modelling frameworks or systems are used to help domain experts and knowledge engineers in eliciting requirements and building conceptual models from a natural language text. In this article, we discuss the state of the art of some recent conceptual modelling frameworks that are based on natural language. We take a closer look at how these frameworks are built, in particular at the underlying motivation, architecture, types of natural language used (e.g., restricted vs. unrestricted), types of the conceptual model generated, verification support of the requirements specifications as well as the conceptual models, and underlying knowledge representation formalism. We also discuss some future research opportunities that these frameworks offer.
引用
收藏
页数:26
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