Ontology based framework to alleviate sparsity first rater and cold start problems from offline technical course recommender systems

Abstract

The academic course selection by students is a problem where information newlineavailable is not sufficient to provide reliable recommendation. For such domains newlinethe recommender systems suffer from challenges like cold-start, sparsity, firstrater and scalability. The proposed work therefore aims to resolve all these newlinecommon problems simultaneously. newlineThe proposed framework is implemented on technical course recommender newlinesystem which will recommend the courses to the students opting for higher studies newlinein technical domain. To make the trust ontology the first requirement is to identify newlinethe entities involved in course selection. The students and faculty members were newlineinterviewed and rigorous literature survey was done to identify the entities and newlinefactors which influence the admissions in technical courses.A total of 118 students newlineand 12 faculty members were interviewed.These factors were then reviewed by newlineexperts and a Google form was prepared. newline