Personality Profiling Using CV Analysis

Abstract

Human personality has been crucial to the growth
of both organizations and individuals. Standard questionnaires
and Curriculum Vitae (CV) analysis are two methods used to
assess human personality. So, a personality prediction system
that combines CV analysis and MBTI model questionnaires to
accurately predict an individual's personality traits based on
their uploaded CV is introduced. The system utilizes advanced
Natural Language Processing (NLP) techniques to extract
relevant information from the CV, including work experience,
education, skills, and achievements. By analysing the textual
content, the system identifies keywords and phrases associated
with different personality traits, laying the foundation for precise
predictions. MBTI model questionnaires are integrated to
further enhance the accuracy of personality prediction. User
responses to the questionnaires are carefully analysed and
mapped to the corresponding personality traits using established
psychological theories and models. A machine learning algorithm
is then employed to create a predictive model, learning from a
pre-labelled dataset of CVs and their associated personality
traits. The system's performance is evaluated using metrics such
as accuracy and precision, ensuring its effectiveness in capturing
the nuances of individual personality traits. The developed
system has significant applications in recruitment and team
composition, aiding employers in making informed hiring
decisions by evaluating candidates whose personalities align with
specific job requirements. Additionally, individuals can benefit
from gaining insights into their own personality traits, enabling
them to make informed career choices and pursue tailored
personal development opportunities. Overall, the proposed
system provides an efficient and accurate approach for
personality prediction based solely on CV analysis and
questionnaire responses.