Ontology is generally defined as an explicit specification of conceptualization which involves the exploration of concepts and its relationships in the domain of interest. Ontology is used to share knowledge across semantic web services, agents and information systems. Therefore the ontology engineer should follow a methodology during the ontology construction to ensure its reliability. This paper presents ontology building methodologies such as Uschold and king [3], Viral Hepatitis Ontology design Methodology [4] and Amaya Berneras et al [9].Moreover the paper presents Rheumatoid and Osteoarthritis ontologies which belong to the medical domain and a proposal for a new methodology applied to build the two medical ontologies. What distinguishes the proposed methodology is the execution of knowledge representation which involves the use of conceptualization and inference rules.
The automated news classification concerns the assignment of news to one or more predefined categories. The automated classified news helps the search engines to mine and categorize the type of news that the user asks for. Most of the researchers focused on the classification of English news and ignore the Arabic news due to the complexity of the Arabic morphology. This article presents a novel methodology to classify the Arabic news. It relies on the use of features extraction and the application of machine learning classifiers which are the Naive Bayes (NB), the Logistic Regression (LR), the Random Forest (RF), the Xtreme Gradient Boosting (XGB), the K-Nearest Neighbors (KNN), the Stochastic Gradient Descent (SGD), the Decision Tree (DT), and the Multi-Layer Perceptron (MLP). The methodology is applied to the Arabic news dataset provided by Mendeley. The accuracy of the classification is more than 95%.
Ontology matching is generally defined as the process of finding correspondences between entities of different ontologies. It can help the data integration between autonomous agents, web services composition, and P2P information sharing. This process is applied through the use of ontology matching tools which use one or more ontology matching techniques. This paper presents tools which have been published in this field, such as Prompt [7], Smatch [5] and Ontobuilder [16]. Moreover the paper illustrates the drawbacks of these tools. New two tools are proposed to handle these drawbacks. The new proposed and other tools are tested using GlycO [8]and EnzyO[10] in the biochemistry field, Osteoarthritis and Rheumatoid in the medical field.
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