Nowadays it is observed that everyone is learning new things to progress in their career through the internet and online courses. Online courses are the best source of learning, and it is helping students, graduate students, and employees to enhance their knowledge and skills. With the increased information on the internet about online courses, it has made it difficult for the learners to make decisions on courses that meet their requirements. A wide range of online courses are available on the internet from different organizers or providers and finding information regarding online courses from many websites is a challenging and time-consuming process. Therefore, we developed an ontology with a common knowledge base that provides a recommendation to help the learners to select the most appropriate course depending on their requirements. For this purpose, classes (subclass and superclass) and their properties (object properties and data properties) with constraints (facets) were defined depending on the scope and domain specified by the Competency Questions (CQs). Next, the ontology was populated with instances to test and check the consistency of the ontology with the reasoner. After testing and querying the ontology using SPARQL in protégé, it is concluded that the ontology developed is consistent and perfectly meets the requirements which were defined by domain to answer the CQs. With this kind of ontology, one can find interesting courses with different categories and get recommendations on courses based on requirements. For the future scope, ontology can include more categories of courses and real instances for a better recommendation.
Ontology-Based Recommender System of Online Courses
