Context-Based Hybrid Semantic Matching Framework for E-mentoring System

In this paper, we propose a context-based hybrid semantic matching framework for e-mentoring system. The framework adopts ontology technologies to define the attributes of mentors and mentees, the matching results, and satisfaction values of the mentoring, and to recommend adequate mentors via semantic reasoning. In the developed ontology named mentoring-matching ontology (M2O), the pairs of mentor-mentee and the satisfaction values of mentoring are managed as cases. To increase the satisfaction of matching, the framework performs rule-based filtering and two kinds of semantic matching to find appropriate mentees and the most similar mentor with the new mentee. We implemented a mobile e-mentoring system named Mint Story with the proposed matching framework. Also, we show the superiority of our framework in the evaluation section.