An intelligent system for modeling and evaluation of domain ontologies for Crystallography as a prospective domain with a focus on their retrieval. (December 2021)

• Record Type: Journal Article
• Authors: Deepak, Gerard; Gulzar, Zameer; Leema, A. Anny
• Is Part Of: Computers & electrical engineering. Volume 96:Part B(2021)
• Publication Date: 2021-12
• Subjects: Crystals -- Crystallography ontology -- Owl representation -- Structure -- Symmetry -- Taxonomy -- Unit cell; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2021.107604
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: Ontological design is a better approach to depict the chosen theory and terms and the related concepts. It is necessary as some theories and terms are quite troublesome for understanding and their relationship within the selected region or field. In this study, Crystallography is chosen as the main field and different approaches were used to build the relationship between the concepts present in it. Ontological phraseology designing is formulated where various concepts within the specific fields are put on and the relationship is coupled among various terms. To execute the designed model, various classes and subclasses within the chosen subject are portrayed using OWL. Furthermore, to represent the network of the chosen subject, the displayed ontological model has been analyzed by utilizing a subjective and measurable approach. A different criterion is studied for subjective examination, and a measurable analysis was performed. The designed model shows a reuse proportion of 87%. The social spider is used for ontology retrieval and the average precision and average accuracy are 93.89% and 95.89%, respectively. An overall F-measure of 97.81% has been achieved for modeling of domain ontologies based on human expert judgment for Crystallography domain.