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A Personalized Ontology Recommendation System to Effectively Support Ontology Development by Reuse

Abdelreheim, Marwa and Soliman, Taysir Hassan A. and Klan, Friederike (2023) A Personalized Ontology Recommendation System to Effectively Support Ontology Development by Reuse. Future Internet, 15 (10), p. 331. Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/fi15100331. ISSN 1999-5903.

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Official URL: https://doi.org/10.3390/fi15100331


The profusion of existing ontologies in different domains has made reusing ontologies a best practice when developing new ontologies. The ontology reuse process reduces the expensive cost of developing a new ontology, in terms of time and effort, and supports semantic interoperability. Existing ontology development tools do not assist in the recommendation of ontologies or their concepts to be reused. Also, existing ontology recommendation tools could suggest whole ontologies covering a set of input keywords without referring to which parts of them (e.g., concepts) can be reused. In this paper, we propose an effective ontology recommendation system that helps the user in the iterative development and reuse of ontologies. The system allows the user to provide explicit preferences about the new ontology, and iteratively guides the user to parts from existing ontologies which match his preferences for reuse. Finally, we developed a prototype of our ontology recommendation system and conducted a user-based evaluation to assess the effectiveness of our approach.

Item URL in elib:https://elib.dlr.de/198010/
Document Type:Article
Title:A Personalized Ontology Recommendation System to Effectively Support Ontology Development by Reuse
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Abdelreheim, MarwaAssiut University, AssiutUNSPECIFIEDUNSPECIFIED
Soliman, Taysir Hassan A.Assiut University, AssiutUNSPECIFIEDUNSPECIFIED
Klan, FriederikeUNSPECIFIEDhttps://orcid.org/0000-0002-1856-7334UNSPECIFIED
Date:7 October 2023
Journal or Publication Title:Future Internet
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In ISI Web of Science:Yes
Page Range:p. 331
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
Keywords:ontology recommendation; ontology reuse; biomedical ontologies; recommender systems
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space System Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Space System Technology
DLR - Research theme (Project):R - MOMENTUM
Location: Jena
Institutes and Institutions:Institute of Data Science > Data Acquisition and Mobilisation
Deposited By: Klan, Dr. Friederike
Deposited On:13 Nov 2023 15:45
Last Modified:17 Nov 2023 09:05

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