Paper Title
Exploring Machine Learning Algorithms for Job Recommendation System

Abstract
Machine learning gives computers the ability to learn without being directly programmed. Machine learning models are proved to be powerful in giving a near perfect solution for complex problems when compared to hard coded methods. Job recommender system automatically gives a list of appropriate and relevant jobs for potential users as well as provides a list of best suited employees to the employers. In order to select the appropriate method to make the system, a relative study of traditional approaches and machine learning methods is done and reported in this paper. It shows how effectively machine learning algorithms can perform compared to the traditional algorithms and other state of art methods. Keywords - Survey, Job Recommendation, Machine Learning, Comparison