Paper Title
Advanced Skill Based Recruitment Portal

Abstract
Due to the corona virus pandemic, the demands of jobs have shifted from offline to online platforms. Still, many students face lots of problems in finding the right kind of job that matches their skill set. They also struggle to search for companies that are not coming to the college. For reducing the manual effort of the students, we proposed an “Advanced Skill Based Recruitment Portal”. Even though in the previous research there exists a variety of approaches and strategies which are used as part of job recommender systems, many of them did not provide proper information to the job seekers. This system helps the students apply for the best on-campus as well as off-campus jobs. The system is a web application that assists students, companies, and placement teams to automate their physical tasks in the recruitment process. The vital feature of this portal is to recommend jobs for off-campus companies based on the skills set of the students. In this paper, we are using max sum similarity and maximal marginal relevance algorithms for recommending jobs according to the skills of the students. Keywords - Job Recommendation, SMS, In-built Security, Skill-based-jobs, large scale application.