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Using Ontology and Rule-Based Reasoning for Conceptual Data Models Synonyms Detection: A Case Study

Using Ontology and Rule-Based Reasoning for Conceptual Data Models Synonyms Detection: A Case Study

Ljubica Kazi, Zoltan Kazi
Copyright: © 2019 |Volume: 30 |Issue: 1 |Pages: 21
ISSN: 1063-8016|EISSN: 1533-8010|EISBN13: 9781522563785|DOI: 10.4018/JDM.2019010101
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MLA

Kazi, Ljubica, and Zoltan Kazi. "Using Ontology and Rule-Based Reasoning for Conceptual Data Models Synonyms Detection: A Case Study." JDM vol.30, no.1 2019: pp.1-21. http://doi.org/10.4018/JDM.2019010101

APA

Kazi, L. & Kazi, Z. (2019). Using Ontology and Rule-Based Reasoning for Conceptual Data Models Synonyms Detection: A Case Study. Journal of Database Management (JDM), 30(1), 1-21. http://doi.org/10.4018/JDM.2019010101

Chicago

Kazi, Ljubica, and Zoltan Kazi. "Using Ontology and Rule-Based Reasoning for Conceptual Data Models Synonyms Detection: A Case Study," Journal of Database Management (JDM) 30, no.1: 1-21. http://doi.org/10.4018/JDM.2019010101

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Abstract

Conceptual data models can change during the information system development and teamwork phases, which require constantly monitoring with synonyms detection. This study elaborates on an approach for detecting synonyms in an entity-relationship model based on mapping with ontological elements. The use of a specific data model validator (DMV) tool enables formalization of the ontology and ER models, as well as their integration with the set of reasoning rules. The reasoning rules enable mapping between formalized elements of the ontology and ER model, and the extraction of synonyms. Formalized elements and reasoning rules are processed within Prolog for the extraction of synonyms. An empirical study conducted by using university student exams demonstrates usability of the proposed approach. The results show effectiveness in extraction of synonyms in all types of conceptual data model elements.

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