Generating ER Diagrams from Requirement Specifications Based On Natural Language Processing

Btoush, Eman S.; Hammad, Mustafa

doi:10.14257/ijdta.2015.8.2.07

Cited by 34 publications

(22 citation statements)

References 13 publications

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“…The most basic heuristics in the literature specify that (1) nouns in a sentence denote an entity, and (2) verbs indicate a potential relationship [10,43]. This prompts us to define the first two heuristics:…”

Section: Entities and Non-hierarchical Relationshipsmentioning

confidence: 99%

Extracting conceptual models from user stories with Visual Narrator

et al. 2017

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Extracting conceptual models from natural language requirements can help identify dependencies, redundancies, and conflicts between requirements via a holistic and easy-to-understand view that is generated from lengthy textual specifications. Unfortunately, existing approaches never gained traction in practice, because they either require substantial human involvement or they deliver too low accuracy. In this paper, we propose an automated approach called Visual Narrator based on natural language processing that extracts conceptual models from user story requirements. We choose this notation because of its popularity among (agile) practitioners and its focus on the essential components of a requirement: Who? What? Why? Coupled with a careful selection and tuning of heuristics, we show how Visual Narrator enables generating conceptual models from user stories with high accuracy. Visual Narrator is part of the holistic Grimm method for user story collaboration that ranges from elicitation to the interactive visualization and analysis of requirements.

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Section: Entities and Non-hierarchical Relationshipsmentioning

confidence: 99%

Extracting conceptual models from user stories with Visual Narrator

et al. 2017

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“…In this stage, the system is decomposed into at least three components. Many approaches are used to extract EER's components from requirement specification, such as [20][21][22]. SEER needs entities and their attributes, relationships, and semantic constraints (condition statements or functions).…”

Section: Details About the Seer-srd Block Diagram Stepsmentioning

confidence: 99%

“…Many methodologies were suggested [20][21][22] to extract entities, their attributes, and relationships among them. These methodologies do not extract condition statements or relative functions.…”

Section: Limitationsmentioning

confidence: 99%

A New Approach for Semantic Integrity Constraints Representation in Enhanced Entity-Relationship and Relational Database Schemas

AlTarawneh¹

2016

IJDTA

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“…A transitive verb determines a relationship between entities (Chen, 1983;Elbendak, 2011;Btoush & Hammad, 2015). A transitive verb is a verb that has a noun to receive an action and a noun to do the action.…”

mentioning

confidence: 99%

“…2. If a preposition such as 'on', 'in', 'by' or 'to' comes after a verb, this may indicate a relationship between entities (Btoush & Hammad, 2015;Omar et al, 2004;Sagar & Abirami, 2014). For example, in the sentence 'An employee works on a project', 'employee' and 'project'…”

mentioning

confidence: 99%

Semi-automated development of conceptual models from natural language text

Omar

Baryannis

2020

Data & Knowledge Engineering

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The process of converting natural language specifications into conceptual models requires detailed analysis of natural language text, and designers frequently make mistakes when undertaking this transformation manually. Although many approaches have been used to help designers translate natural language text into conceptual models, each approach has its limitations. One of the main limitations is the lack of a domain-independent ontology that can be used as a repository for entities and relationships, thus guiding the transition from natural language processing into a conceptual model. Such an ontology is not currently available because it would be very difficult and time consuming to produce. In this thesis, a semiautomated system for mapping natural language text into conceptual models is proposed. The model, which is called SACMES, combines a linguistic approach with an ontological approach and human intervention to achieve the task.

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Generating ER Diagrams from Requirement Specifications Based On Natural Language Processing

Abstract: An Entity Relationship (ER)

Cited by 34 publications

References 13 publications

Extracting conceptual models from user stories with Visual Narrator

Extracting conceptual models from user stories with Visual Narrator

A New Approach for Semantic Integrity Constraints Representation in Enhanced Entity-Relationship and Relational Database Schemas

Semi-automated development of conceptual models from natural language text

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