الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
Ontologies provide a powerful method for representing, reusing, and sharing domain knowledge. They are extensively used in a wide range of disciplines, including artificial intelligence, knowledge engineering, biomedical informatics, and many more. For several reasons, developing domain ontologies is a challenging task. One of these reasons is that it is a complicated and time-consuming process.
Multiple ontology development methodologies have already been proposed. However, there is room for improvement in terms of covering more activities during development (such as enrichment) and enhancing others (such as conceptualization).
In this thesis, an enhanced ontology development methodology (ODCM-ODM) is proposed. Ontology-driven conceptual modeling (ODCM), ontology matching and natural language processing (NLP) serve as the foundation of the proposed methodology. ODCM is defined as the utilization of ontological ideas from various areas to build engineering artifacts that improve conceptual modeling. Ontology matching is a promising approach to overcome the semantic heterogeneity challenge between different ontologies. And NLP refers to the scientific discipline that employs computer techniques to analyze human language.
The proposed ODCM-ODM is applied to build ontologies in two different domains (e-government and tourism), which can be beneficial for a variety of applications. The produced e-government ontology is compared with 20 existing ontologies from the same domain. Based on OntoMetrics, the average values of metrics correlated to accuracy, understandability, cohesion and conciseness lie in the 95th, 95th, 95th and 57th percentiles respectively. On the other hand, the tourism ontology is evaluated based on competency questions (CQs) and quality metrics. It is verified that the ontology answers SPARQL queries covering all CQ groups specified by domain experts. Quality metrics are used to compare the produced ontology with four existing tourism ontologies. For instance, according to the metrics related to conciseness, the produced ontology received a first place ranking when compared to the others, whereas it received a second place ranking regarding understandability. The results are encouraging and show that utilizing ODCM could improve and facilitate the ontology development process.