Application of K-Means Clustering Algorithm to Determine the Density of Demand of Different Kinds of Jobs

Abstract

In the current competitive job market, information is the most powerful tool. As a job, the seeker looks for a job, and he must have the insight of what kind of competition he is about to face. This information will allow the job seeker to improve himself from the rest in the market. To determine the demand for any field of job among job seekers, with the help of the unsupervised k-means machine learning algorithm, the data of job interests can be clustered in different groups based on their kinds. The visual representation of the clusters in a scatter plot gives the information on which variety of jobs are in more or less demand among job seekers with the density of the groups. This study provides insight into the current jobmarket.