An Ontology-based Decision Support System for Multi-objective Prediction Tasks

Student profile modeling is a topic that continues to attract the interest of both academics and researchers because of its crucial role in the development of predictive or decision support systems. It provides platforms to build intelligent systems such as e-orientation, e-recruitment, recommendation, and prediction systems. The purpose of this research is to propose an ontology-based decision support system that can be used for multi-objective prediction tasks such as prediction of failure/abundance, orientation or decision-making. Two major contributions are proposed here: a new domain ontology that models the profile of a student and a system that is based on this ontology to perform multiple prediction tasks. The proposed approach relies on the efficiency of the ontology to ensure semantic interoperability and the benefits of machine learning techniques to build an intelligent system for a multipurpose decision support objectives. The proposed system uses Decision Tree algorithm (C5.0), but other machine learning models can be added if they prove to be more efficient. Furthermore, the performance of the developed method is computed using performance metrics and achieved 83.6% for accuracy and 81.9% for recall.