Towards Definition of a Unified Domain Meta-model

Hnatkowska, Bogumiła; Walkowiak-Gall, Anita

doi:10.1007/978-3-319-99617-2_6

Cited by 4 publications

(3 citation statements)

References 2 publications

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“…While implicit information hidden in complex statements are usually neglected. As well, further information should be identified to increase the understanding and usefulness of extracted vocabulary, in particular: descriptions (definitions) and synonyms 9 . Moreover, much of the literature tended to extract concepts according to no standard, missing the opportunity to benefit from the reusability and this is what we try to overcome in this paper.…”

Section: Related Workmentioning

confidence: 98%

“…The terminology is generally presented as a Glossary, Definition, or Domain model, 3 and usually not easily understood by non‐IT people or hardly integrated in heterogeneous system because of its formal language or its non‐standard format. However, the vocabulary of a specific domain, frequently termed “concept model,” 7 or “business vocabulary,” 8 should be formally defined, supported with textual descriptions and synonyms 9 …”

Section: Introductionmentioning

confidence: 99%

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Automated generation of terminological dictionary from textual business rules

Haj

Balouki

Gadi

2021

J Software Evolu Process

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To support decision making, organizations tend to operate according to Business Rules, which are usually represented in a natural language format easily understood by all intervenors. According to the business rules manifesto by the Business Rules Group (OMG), rules build on facts, and facts build on concepts as expressed by terms. To avoid ambiguity and misunderstanding, the standardization of the terminology used at the business level becomes a persistent need. However, doing so manually is error prone and time consuming, especially that the Business Rules are the subject of continuous updating. In this paper, we present an automated approach to generate the Business Vocabulary from textual statements of Business Rules. Our approach is distinguished from existing works in that it extracts the Terminological Dictionary as described by the Semantic of Business Vocabulary and Rules (SBVR) standard to provide a more comprehensive meaning for each concept. Accordingly, an in‐depth Natural Language Processing (NLP) is used to extract not only flat list of terms and relations, but also extra specifications and implicit knowledge. With a satisfactory result, our approach has proved its capability to automatically generate the SBVR Terminological Dictionary from large number of natural language business rules statements.

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Section: Related Workmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Automated generation of terminological dictionary from textual business rules

Haj

Balouki

Gadi

2021

J Software Evolu Process

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show abstract

“…While implicit information hidden in complex statements are usually neglected. As well, further information should be identified to increase the understanding and usefulness of extracted vocabulary, in particular: definitions and synonyms [30]. However, no one as far as we know has generated a more complete SBVR model from unrestricted BR statements as our approach does.…”

Section: Automaticmentioning

confidence: 99%

The Semantic of Business Vocabulary and Business Rules: An Automatic Generation From Textual Statements

et al. 2021

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In the early phases of the software development process, specifications are mostly written in a natural language rather than formal models, which is not supported by the Model Driven Architecture (MDA). For this reason, the Semantic of Business Vocabulary and Rules (SBVR) is proposed by the Object Management Group to represent the textual specifications in a language comprehensible by both of humans and machines, to facilitate its integration in the MDA lifecycle. However, businesspeople are usually not familiar with SBVR standard. In this paper we present an approach to automatically transform textual business rules to an SBVR model, to facilitate its integration in nowadays information technology infrastructures. Our approach is distinguished from existing works in that it uses an in-depth Natural Language Processing to extract a more comprehensible SBVR model that includes the semantic formulation of each business rule statement, coupled with a Terminological Dictionary of extracted concepts, to which we have added further specifications such as definitions and synonyms. The evaluation of our approach shows that for three sets of business rules statements taken from different domains, we could generate the correct meaning with an average of F1-score exceeding 87%.

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Compatibility Checking of Business Rules Expressed in Natural Language Against Domain Specification

Hnatkowska

2021

Advances in Computational Collective Intelligence

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Towards Definition of a Unified Domain Meta-model

Cited by 4 publications

References 2 publications

Automated generation of terminological dictionary from textual business rules

Automated generation of terminological dictionary from textual business rules

The Semantic of Business Vocabulary and Business Rules: An Automatic Generation From Textual Statements

Compatibility Checking of Business Rules Expressed in Natural Language Against Domain Specification

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