Harmonic Means between TF-IDF and Angle of Similarity to Identify Prospective Applicants in a Recruitment Setting

Abstract

Recruitment industry is better and bigger than ever. There is no denying that technology plays a major role in helping recruiters evolve and adopt with the pace of recruitment on a global scale. With the increasing population, the demand for manpower has been relative to the growth and challenging needs of recruiters; be it online or traditional way of outsourcing. In this study, we propose a combination of angle or similarity and term frequency–inverse document frequency to easily classify prospective job applicants. The results show that the two models are relative to each other, value-wise and harmonic means. Their values are synchronized to a certain extent based on our query. This is helpful because recruiters may save a lot of time in classifying prospective applicants. It can also be concluded that harmonic similarity is viable in combining the two models. As a future work, it is possible to develop a full featured application to be deployed in a production setting.