• Ms.Sharmila Shankar Patil
• Mr.Suraj.S.Redekar

Increased urbanization has resulted in a significant rise in work opportunities. As a result, a broad organization has evolved, necessitating the employment of a diversified workforce. Organizations advertise job openings in order to recruit talented and helpful employees. Most of the time, the firm receives an excessive number of job applications due to high demand and an insufficient quantity of available positions, as well as rising unemployment. Companies have a tremendous incentive to hire the person with the most personality. Choosing from the massive quantity of resumes or curriculum vitae received is a challenging task. As a result, the development of an efficient and reliable automated personality rating system is necessary. For the objective of a CV content extraction system, a few ways have been investigated. A number approaches have been examined in order to achieve the goal of a CV content extraction system. The bulk of these approaches have faults that must be addressed. As a result, the relevant research on the CV data extraction methodology is performed to achieve the presented approach that utilizes Bag of Words, TF-IDF and Deep Belief Networks along with Decision Making and Protocol Mapping. The approach has been elaborated to achieve the improved analysis of the CVs which has been quantified using effective experimentation that has resulted in highly satisfactory results.

Curriculum Vitae, Natural Language Processing, Bag of Words, Term Frequency, Inverse Document Frequency, Deep Belief Network, Decision Making and Protocol Mapping.

"Enriching Personality Classification through Analysis of CV using NLP and Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 9, page no.c663-c670, September-2022, Available :http://www.jetir.org/papers/JETIR2209300.pdf

"Enriching Personality Classification through Analysis of CV using NLP and Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 9, page no. ppc663-c670, September-2022, Available at : http://www.jetir.org/papers/JETIR2209300.pdf