SBVR Business Rules Generation from Natural Language Specification
SBVR Business Rules Generation from Natural Language Specification
复制标题
根据自然语言规范生成 SBVR 业务规则
DOI：
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发表时间：
2011
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通讯作者：
B. Bordbar
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作者：
Imran Sarwar Bajwa;Mark G. Lee;B. Bordbar
在本文中，我们提出了一种新的方法，翻译自然语言规格说明SBVR业务规则。业务规则约束业务结构或控制业务流程的行为。在现代业务建模中，一个重要的阶段是编写业务规则。通常，业务规则分析人员必须以自然语言（NL）手动编写数百条业务规则，然后根据需要以特定规则语言（如SBVR或OCL）手动翻译所有规则的NL规范。然而，人工翻译NL规则规范的正式表示为SBVR规则不仅是困难的，复杂的和耗时的，而且可能导致错误的业务规则。在本文中，我们提出了一个自动化的方法，自动翻译NL（如英语）规范的业务规则SBVR（语义业务词汇和规则）规则。从自然语言到标准语言的翻译面临的主要挑战是复杂的英语语义分析。我们已经使用了基于规则的算法，强大的英语语义分析和生成SBVR规则。基于SBVR的业务规则的自动生成可以帮助在典型的业务建模中改进和有效地约束业务方面。
In this paper, we present a novel approach of translating natural languages specification to SBVR business rules. The business rules constraint business structure or control behaviour of a business process. In modern business modelling, one of the important phases is writing business rules. Typically, a business rule analyst has to manually write hundreds of business rules in a natural language (NL) and then manually translate NL specification of all the rules in a particular rule language such as SBVR, or OCL, as required. However, the manual translation of NL rule specification to formal representation as SBVR rule is not only difficult, complex and time consuming but also can result in erroneous business rules. In this paper, we propose an automated approach that automatically translates the NL (such as English) specification of business rules to SBVR (Semantic Business Vocabulary and Rules) rules. The major challenge in NL to SBVR translation was complex semantic analysis of English language. We have used a rule based algorithm for robust semantic analysis of English and generate SBVR rules. Automated generation of SBVR based Business rules can help in improved and efficient constrained business aspects in a typical business modelling.