Scope prediction utilizing support vector machine for career opportunities

Abstract

Education courses were offered at tutorial establishments round the world. In the present educational society, choosing a career path can be stressful and overwhelming. Selecting the right course for the career is the most crucial decision to make and can be troublesome if not guided properly. The purpose of choosing the appropriate course in any college with employment facilities is the major drawback in the existing system. The conventional method will only give the information about the course. The data is predicted by analyzing the frequent searching pattern of the user by matrix factorization method. To overcome those anomalies, this paper proposes the Course prediction techniques for the student which uses the Base Linear Regression (BLR) Algorithm to predict the course. This algorithm comes under the Support Vector Machine (SVM) Algorithm that will process the data set about the various courses. The student will initially register their details before logging in to the website. This application will filter the data based on their educational qualification when the student login to the homepage. Content Based Filtering (CBF) technique is applied further to filter the data in dataset. This will sort out the information based on the user requirements so that the student can choose the course that they need to study with the accurate predicted data with their future growth in the graphical form.