A Study of Machine Learning Based Approaches to Extract Personality Information from Curriculum Vitae

Curriculum Vitae (CV) is an essential document for a person to obtain a suitable job in a company. The main purpose of a CV is to create a profound impression on the recruiters which helps to attract their attention. CV also acts as the first communication between a person and the recruiter before the job is offered and the candidate is proceeded to the next stage. Personalities are very important when it comes to job hiring for a company. Most of the experienced recruiters can determine the candidates' personalities before conducting an interview session by going through the content of the CV. Employers always sought for the most suitable candidates with dynamic personalities for the relevant job positions to ensure good productivity and job performance. Therefore, personality assessment tests are conducted by the job recruiters to find the suitable candidates for the vacant positions in their company/organization. The drawback for the traditional hiring process is the large amount of time taken to process numerous applications. To save the time of both job recruiters and applicants, authors have conducted this research that allows the CV to be extracted by utilizing machine learning algorithms to obtain the vital information needed to evaluate the applicants' personalities. The research presents experimental study for the effectiveness of the selected algorithms towards extracting personality traits from the CV. Based on the experimental evaluation, the effectivity of the algorithms is discussed with statistical evidences.