A Simple Recommender Engine for Matching Final-Year Project Student with Supervisor
This addresses a domain-specific problem for final-year students and supervisors, but it is incremental as it applies an existing method to a new dataset.
The paper tackled the problem of matching final-year project students with supervisors by developing a simple recommender engine based on Euclidean distance, using questionnaire data in CSV format and implemented in Java, with initial tests showing feasibility and potential to solve the matching issue.
This paper discusses a simple recommender engine, which can match final year project student based on their interests with potential supervisors. The recommender engine is constructed based on Euclidean distance algorithm. The initial input data for the recommender system is obtained by distributing questionnaire to final year students and recording their response in CSV format. The recommender engine is implemented using Java class and application, and result of the initial tests has shown promises that the project is feasible to be pursued as it has the potential of solving the problem of final year students in finding their potential supervisors.