Scoring of Resume and Job Description Using Word2vec and Matching Them Using Gale–Shapley Algorithm

Abstract

The paper introduces a quick-witted system that assists employers to find the right candidate for a job and vice-versa. Multiple approaches have to be taken into account for parsing, analyzing, and scoring documents (CV, vacancy details). However, In this paper, we have devised an approach for ranking such documents using word2vec algorithm and matching them to their appropriate pair using Gale–Shapley algorithm. When ranking a CV, different cases are taken into consideration: skills, experience, education, and location. The ranks are then used to find an appropriate match of employers and employees with the use of Gale–Shapley algorithm which eases companies for higher best possible candidates. The methods experimented for the scoring, and matching is explained below on the paper.