Knowledge Graph Based Recommender System for an Academic Domain - A Proposal

Recommendation systems has simplified decision making phase in many instances. The paper seeks to help the interested candidate looking to incorporate semantics, knowledge-graph, and ontology. Literature reviews were presented deriving the research question which seeks answers on the question how can we fit-in ensemble learning to ontology in mapping the research scholars with common interest areas of research? It has been determined that creating the ontology of the researchers or experts with the highest acceptance and frequency of engagement is the most acceptable approach. As a result, we propose a system that first establishes the cluster, then discovers the highest-ranking member in the cluster, and then creates ontologies based on that to recommend to new users, and then exposes them to the public domain as RDF using the neo4j plugin. This is a proposal only and further exploration is required.