{"title":"Prediction of Personality Traits and Suitable Job through an Intelligent Interview Agent using Machine Learning","authors":"Ch. Mandakini","doi":"10.37624/jcsa/15.1.2023.21-31","DOIUrl":null,"url":null,"abstract":"Abstract: Interviews play a crucial role in an individual’s career. They are often a means through which recruitments are finalized in various companies. To effectively understand the suitability of the candidate for a particular job, the interviewer not only assesses the conceptual knowledge of the candidate but also tries to identify if the personality traits of the prospect match with the job requirements. Facial expressions are crucial in human communication since they assist in understanding others better and are commonly used to assess personality. The automation ensures that the procedure for selecting candidates in an objective manner is not tainted by the interviewer's bias and personal experiences. The proposed Intelligent Interview Agent uses video input of the interviewee to predict the Big Five Personality traits as seen by skilled human resource experts. To achieve this, the system uses VGG16 Convolutional Neural Network (CNN) Model. The system also predicts the suitable job role for the candidate depending on the scores predicted for the Big Five personality traits, by employing a machine learning (ML) model. The system serves the purpose of both the recruiter and the candidate. The recruiter can analyse the candidate’s personality traits and assign him/her the predicted suitable job. On the other hand, the candidate can get an idea of his/her personality traits and know which profession suits the best.","PeriodicalId":39465,"journal":{"name":"International Journal of Computer Science and Applications","volume":"5 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computer Science and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37624/jcsa/15.1.2023.21-31","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract: Interviews play a crucial role in an individual’s career. They are often a means through which recruitments are finalized in various companies. To effectively understand the suitability of the candidate for a particular job, the interviewer not only assesses the conceptual knowledge of the candidate but also tries to identify if the personality traits of the prospect match with the job requirements. Facial expressions are crucial in human communication since they assist in understanding others better and are commonly used to assess personality. The automation ensures that the procedure for selecting candidates in an objective manner is not tainted by the interviewer's bias and personal experiences. The proposed Intelligent Interview Agent uses video input of the interviewee to predict the Big Five Personality traits as seen by skilled human resource experts. To achieve this, the system uses VGG16 Convolutional Neural Network (CNN) Model. The system also predicts the suitable job role for the candidate depending on the scores predicted for the Big Five personality traits, by employing a machine learning (ML) model. The system serves the purpose of both the recruiter and the candidate. The recruiter can analyse the candidate’s personality traits and assign him/her the predicted suitable job. On the other hand, the candidate can get an idea of his/her personality traits and know which profession suits the best.
期刊介绍:
IJCSA is an international forum for scientists and engineers involved in computer science and its applications to publish high quality and refereed papers. Papers reporting original research and innovative applications from all parts of the world are welcome. Papers for publication in the IJCSA are selected through rigorous peer review to ensure originality, timeliness, relevance, and readability.