A fuzzy ontology modeling for case base knowledge in diabetes mellitus domain
Knowledge-Intensive Case-Based Reasoning Systems (KI-CBR) mainly depend on ontologies. Ontology can play the role of case-base knowledge. The combination of ontology and fuzzy logic reasoning is critical in the medical domain. Case-base representation based on fuzzy ontology is expected to enhance t...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Elsevier
2017-06-01
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| Series: | Engineering Science and Technology, an International Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2215098616313763 |
| _version_ | 1818560629804367872 |
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| author | Shaker El-Sappagh Mohammed Elmogy |
| author_facet | Shaker El-Sappagh Mohammed Elmogy |
| author_sort | Shaker El-Sappagh |
| collection | DOAJ |
| description | Knowledge-Intensive Case-Based Reasoning Systems (KI-CBR) mainly depend on ontologies. Ontology can play the role of case-base knowledge. The combination of ontology and fuzzy logic reasoning is critical in the medical domain. Case-base representation based on fuzzy ontology is expected to enhance the semantic and storage of CBR knowledge-base. This paper provides an advancement to the research of diabetes diagnosis CBR by proposing a novel case-base fuzzy OWL2 ontology (CBRDiabOnto). This ontology can be considered as the first fuzzy case-base ontology in the medical domain. It is based on a case-base fuzzy Extended Entity Relation (EER) data model. It contains 63 (fuzzy) classes, 54 (fuzzy) object properties, 138 (fuzzy) datatype properties, and 105 fuzzy datatypes. We populated the ontology with 60 cases and used SPARQL-DL for its query. The evaluation of CBRDiabOnto shows that it is accurate, consistent, and cover terminologies and logic of diabetes mellitus diagnosis. |
| first_indexed | 2024-12-14T00:40:44Z |
| format | Article |
| id | doaj.art-d1a1848f9c8f4bf48a468211eed55799 |
| institution | Directory Open Access Journal |
| issn | 2215-0986 |
| language | English |
| last_indexed | 2024-12-14T00:40:44Z |
| publishDate | 2017-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Engineering Science and Technology, an International Journal |
| spelling | doaj.art-d1a1848f9c8f4bf48a468211eed557992022-12-21T23:24:22ZengElsevierEngineering Science and Technology, an International Journal2215-09862017-06-012031025104010.1016/j.jestch.2017.03.009A fuzzy ontology modeling for case base knowledge in diabetes mellitus domainShaker El-Sappagh0Mohammed Elmogy1Faculty of Computers & Information, Minia University, EgyptFaculty of Computers & Information, Mansoura University, EgyptKnowledge-Intensive Case-Based Reasoning Systems (KI-CBR) mainly depend on ontologies. Ontology can play the role of case-base knowledge. The combination of ontology and fuzzy logic reasoning is critical in the medical domain. Case-base representation based on fuzzy ontology is expected to enhance the semantic and storage of CBR knowledge-base. This paper provides an advancement to the research of diabetes diagnosis CBR by proposing a novel case-base fuzzy OWL2 ontology (CBRDiabOnto). This ontology can be considered as the first fuzzy case-base ontology in the medical domain. It is based on a case-base fuzzy Extended Entity Relation (EER) data model. It contains 63 (fuzzy) classes, 54 (fuzzy) object properties, 138 (fuzzy) datatype properties, and 105 fuzzy datatypes. We populated the ontology with 60 cases and used SPARQL-DL for its query. The evaluation of CBRDiabOnto shows that it is accurate, consistent, and cover terminologies and logic of diabetes mellitus diagnosis.http://www.sciencedirect.com/science/article/pii/S2215098616313763Case-based reasoningSemantic retrievalCase base representationFuzzy ontologyDiabetes diagnosis |
| spellingShingle | Shaker El-Sappagh Mohammed Elmogy A fuzzy ontology modeling for case base knowledge in diabetes mellitus domain Engineering Science and Technology, an International Journal Case-based reasoning Semantic retrieval Case base representation Fuzzy ontology Diabetes diagnosis |
| title | A fuzzy ontology modeling for case base knowledge in diabetes mellitus domain |
| title_full | A fuzzy ontology modeling for case base knowledge in diabetes mellitus domain |
| title_fullStr | A fuzzy ontology modeling for case base knowledge in diabetes mellitus domain |
| title_full_unstemmed | A fuzzy ontology modeling for case base knowledge in diabetes mellitus domain |
| title_short | A fuzzy ontology modeling for case base knowledge in diabetes mellitus domain |
| title_sort | fuzzy ontology modeling for case base knowledge in diabetes mellitus domain |
| topic | Case-based reasoning Semantic retrieval Case base representation Fuzzy ontology Diabetes diagnosis |
| url | http://www.sciencedirect.com/science/article/pii/S2215098616313763 |
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