AUTOMATED PERSONALITY PREDICTIVE MODEL FOR E-RECRUITMENT USING LOGISTIC REGRESSION TECHNIQUE
Abstract
Human personality plays a vital role in individual's life as well as in the development of an organization. Common ways to evaluating human personality is by using standard questionnaires or by analyzing the Curriculum Vitae (CV). Traditionally, recruiters manually shortlist/filters a candidate’s CV as per their requirements. In this work, a system that automates the eligibility check and aptitude evaluation of candidates in a recruitment process is developed. To meet this need an automated system module is developed for the analysis of aptitude or personality test based on candidate’s CV. The work presented in this paper determines the personality trait of applicants through CV analysis using Python upon which the Personality prediction Model is built. The result helps in evaluating the qualities in the candidates by analyzing personality trait and character of such candidate. The system provides serves as a better option for the recruitment process so that candidate’s data can extracted from CV and shortlisted for the best decision via fair judgment.
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References
[2] De Raad, B. (2000). The Big Five Personality Factors: The psycholexical approach to personality. Hogrefe & Huber Publishers.
[3] Barber, B. M., & Odean, T. (2008). All that glitters: The effect of attention and news on the buying behavior of individual and institutional investors. The review of financial studies, 21(2), 785-818.
[4] Manasi Ombhase, Student, PCE, Prajakta Gogate, Student, PCE, Tejas Patil, Student, PCE, Karan Nair, Student, PCE and Prof. Gayatri Hegde, Faculty, PCE, “Automated Personality Classification Using Data Mining Techniques”
[5] Donnelley, R. R., & Fitzmaurice, M. (2006). Designing Modules For Learning Pp. 99-110 O’neil, G., Moore, S, Mc. Mullin, B. Emerging Issues In The Practice Of University Learning And Teaching.
[6] Rynes, S. L., Gerhart, B., & Minette, K. A. (2004). The importance of pay in employee motivation: Discrepancies between what people say and what they do. Human Resource Management: Published in Cooperation with the School of Business Administration, The University of Michigan and in alliance with the Society of Human Resources Management, 43(4), 381-394.
[7] Wanous, M., Procter, B., & Murshid, K. (2009). Assessment for learning and skills development: The case of large classes. European Journal of Engineering Education, 34(1), 77-85.
[8] https://www.kaggle.com/datasets
[9] Stoltzfus, J. C. (2011). Logistic regression: a brief primer. Academic emergency medicine, 18(10), 1099-1104.
[10] Darlington RB. Regression and Linear Models. Columbus, OH: McGraw-Hill Publishing Company, 1990.
[11] Tabachnick BG, Fidell LS. Using Multivariate Statistics. 5th ed. Boston, MA: Pearson Education, Inc., 2007.
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