Contextual Ontology-Based Feature Selection for Teachers

The context of teacher is indescribable without considering the multiple overlapping contextual situations. Teacher Context Ontology (TCO) presents a unified representation data these contexts. This ontology provides relatively high number features to consider for each context. These result in computational overhead during processing context-aware recommender systems. Therefore, most relevant must be favored over others losing any potential ones using feature selection approach. existing approaches provide struggling results with features. In this paper, new ontology-based approach introduced. finds similar contexts insertion representation. Also, it selects from according their corresponding importance variance-based novel terms representation, selection, and deriving implicit relationships teacher.