Recommender System For Educational Analysis In Prediction of Appropriate Career & Domain Recommendations using Machine Learning Techniques

Abstract

These days Career and Domain options have always been a very big ambiguous decision-making process for many prospective aspirants. Many aspirants make substantial domain changes very late in their career which may result in drastic effects on their career as well as their financial status. Many reports suggested that companies have suffered huge losses because of making wrong choices regarding the domain and employee interest. Hence providing a common platform early in the education sector for both the aspirants as well as companies that would provide appropriate domain suggestions for aspirants as well as right employee choices for companies would be highly beneficial that could help in generating better results when compared to the traditional ways of career choices employment. In this research, we are proposing a recommender system based model that would bridge the gap and help in formulating future needs