2016
DOI: 10.4018/ijeis.2016040101
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Knowledge-Based Systems for Data Modelling

Abstract: Data modelling is a complex process that depends on the knowledge and experience of the designers who carry it out. The quality of created models has a significant impact on the quality of successive phases of information systems development. This paper, in short, reviews the data modelling process, the entity-relationship method (ERM) and actors in the data modelling process. Further, in more detail it presents systems, methods, and tools for the data modelling process and identifies problems that occur durin… Show more

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Cited by 5 publications
(5 citation statements)
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References 36 publications
(35 reference statements)
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“…We use the artefacts (corpus-based lexicon and CEN PSG-Phrase structure grammar) from previous works [1,46] to obtain valid BD sentences that represent the system input. The MULTEXT-East lexicon and its morpho-syntactic descriptions are used because it covers a broad range of syntax categories and supports the Croatian language (planned in further research).…”
Section: Previous Work Artefactsmentioning
confidence: 99%
See 1 more Smart Citation
“…We use the artefacts (corpus-based lexicon and CEN PSG-Phrase structure grammar) from previous works [1,46] to obtain valid BD sentences that represent the system input. The MULTEXT-East lexicon and its morpho-syntactic descriptions are used because it covers a broad range of syntax categories and supports the Croatian language (planned in further research).…”
Section: Previous Work Artefactsmentioning
confidence: 99%
“…All BD sentences were formulated to be syntactically correct according to the specific grammar rules (presented in Table 1 of Section 2.4). The phrase structure grammar for BDs and the data model language (EARC; entity attribute relationship cardinalities language) are described in papers [1,2].…”
Section: Introductionmentioning
confidence: 99%
“…There are many commercial graphical CASE tools which can be used to automatically convert a conceptual model into a logical or physical model (Thonggoom, 2011). However, there is no commercial or noncommercial tool which can automatically convert natural language text into a conceptual model (Song, Zhu, Ceong, & Thonggoom, 2015;Šuman, Jakupović, & Kuljanac, 2016;Thonggoom, 2011). Instead, various semi-automated approaches are used for this purpose, which include the following (Thonggoom, 2011).…”
Section: Natural Language Specification Problemsmentioning
confidence: 99%
“…Conversely, knowledge-based approaches such as the pattern-based, case-based and ontology-based approaches do need a set of linguistic rules extracted from a linguistic approach to guide the process of extraction of CMs from natural language text, since there is no domain-independent knowledge designed to support the creation of conceptual models. Furthermore, because of natural language ambiguities, and the fact that fully-automated extraction of conceptual models from natural language is not possible (Song et al, 2015;Šuman et al, 2016;Thonggoom, 2011), integrated approaches need to be supported by a minimum level of human intervention to help in solving ambiguities in natural language text. An integrated approach supported by a minimum level of human intervention would therefore help in producing a semi-automated tool to guide the process of extracting and producing conceptual models from natural language specifications.…”
Section: Table 21 Comparison Between Approaches Used For Extracting mentioning
confidence: 99%
“…Previous papers 1,2 have described the development phases for creating a phrase structure grammar (PSG) for BDs as well as for the EARC (entity attribute relationship cardinalities) data-modeling language. Their definitions were a prerequisite for creating translation rules for automated translation.…”
Section: Introductionmentioning
confidence: 99%